Deliberation on Design Strategies of Automatic Harvesting Systems: A Survey
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paper_title: Robotics for Plant Production

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Applying robotics in plant production requires the integration of robot capabilities, plant culture, and the work environment. Commercial plant production requires certain cultural practices to be performed on the plants under certain environmental conditions. Some of the environmental conditions are mostly natural and some are modified or controlled. In many cases, the required cultural practices dictate the layout and materials flow of the production system. Both the cultural and environmental factors significantly affect when, where and how the plants are manipulated. Several cultural practices are commonly known in the plant production industry. The ones which have been the subject of robotics research include division and transfer of plant materials in micropropagation, transplanting of seedlings, sticking of cuttings, grafting, pruning, and harvesting of fruit and vegetables. The plants are expected to change their shape and size during growth and development. Robotics technology includes many sub-topics including the manipulator mechanism and its control, end-effector design, sensing techniques, mobility, and workcell development. The robots which are to be used for performing plant cultural tasks must recognize and understand the physical properties of each unique object and must be able to work under various environmental conditions in fields or controlled environments. This article will present some considerations and examples of robotics development for plant production followed by a description of the key components of plant production robots. A case study on developing a harvesting robot for an up-side-down single truss tomato production system will also be described.
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paper_title: Mechanical harvesting of California table and oil olives

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Mechanical harvesting must be developed for successful table and olive oil production in California. Both canopy contact shaking head and trunk shaking harvesters can produce processed black ripe olives that trained sensory panels and consumer panels cannot distinguish from hand-harvested olives. However, both types of harvesters remove and capture less than the 80% efficiency required for economically feasible mechanical table olive harvesting. The harvesters differ in their removal patterns, efficiency, and types of tree damage. No successful abscission compounds to decrease fruit removal force have been identified. Therefore, as with oil oli- ves, the tree shape must be modified for successful mechanical table olive harvesting. Recent results demonstra- te training to an espalier shape, with and without a trellis, in high density hedgerows, does not decrease yield. These espaliered hedgerow orchards can be harvested with both canopy contact and trunk shakers. Therefore, the traditional California table olive industry must adapt a modified version of the high density and super high density orchards, designed specifically for mechanical harvesting, now being developed for olive oil production in California.
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paper_title: Image change detection algorithms: a systematic survey

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Detecting regions of change in multiple images of the same scene taken at different times is of widespread interest due to a large number of applications in diverse disciplines, including remote sensing, surveillance, medical diagnosis and treatment, civil infrastructure, and underwater sensing. This paper presents a systematic survey of the common processing steps and core decision rules in modern change detection algorithms, including significance and hypothesis testing, predictive models, the shading model, and background modeling. We also discuss important preprocessing methods, approaches to enforcing the consistency of the change mask, and principles for evaluating and comparing the performance of change detection algorithms. It is hoped that our classification of algorithms into a relatively small number of categories will provide useful guidance to the algorithm designer.
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paper_title: Automatic fruit recognition: a survey and new results using Range/Attenuation images

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An automatic fruit recognition system and a review of previous fruit detection work are reported. The methodology presented is able to recognize spherical fruits in natural conditions facing difficult situations: shadows, bright areas, occlusions and overlapping fruits. The sensor used is a laser range-finder giving range/attenuation data of the sensed surface. The recognition system uses a laser range-finder model and a dual color/shape analysis algorithm to locate the fruit. The three-dimensional position of the fruit, radius and the reflectance are obtained after the recognition stages. Results for a set of artificial orange tree images and real-time considerations are presented.
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paper_title: Stability tests of two-finger tomato grasping for harvesting robots

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In this study, the theories of spatial and contact grasp stability were extended and integrated into a whole system, and then a vision processing approach that extracts the relevant information for synthesising plate and curved finger grasps for unknown tomato fruits from tomato images was presented. Finally, stability tests involving grasping tomatoes with two parallel fingers were performed using two types of fingers (plate and curved fingers). Existing theories of grasp stability related to rigid objects could be integrated and extended to analyse the grasping stability for half-ripe tomatoes. Curved fingers were more suitable for stably grasping tomatoes than were plate fingers. The prediction method of stable grasp regions can be regarded as a potential strategy (algorithm) for achieving a programmed control of two-fingered tomato grasp stability based on vision feedback. Visual perception is used to reduce the uncertainty and obtain relevant geometric information about the tomatoes during harvesting.
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paper_title: Interactive teaching of task-oriented robot grasps

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This paper focuses on the problem of grasp stability and grasp quality analysis. An elegant way to evaluate the stability of a grasp is to model its wrench space. However, classical grasp quality measures suffer from several disadvantages, the main drawback being that they are not task related. Indeed, constructive approaches for approximating the wrench space including also task information have been rarely considered. This work presents an effective method for task-oriented grasp quality evaluation based on a novel grasp quality measure. We address the general case of multifingered grasps with point contacts with friction. The proposed approach is based on the concept of programming by demonstration and interactive teaching, wherein an expert user provides in a teaching phase a set of exemplar grasps appropriate for the task. Following this phase, a representation of task-related grasps is built. During task planning and execution, a grasp could be either submitted interactively for evaluation by a non-expert user or synthesized by an automatic planning system. Grasp quality is then assessed based on the proposed measure, which takes into account grasp stability along with its suitability for the task. To enable real-time evaluation of grasps, a fast algorithm for computing an approximation of the quality measure is also proposed. Finally, a local grasp optimization technique is described which can amend uncertainties arising in supplied grasps by non-expert users or assist in planning more valuable grasps in the neighborhood of candidate ones. The paper reports experiments performed in virtual reality with both an anthropomorphic virtual hand and a three-fingered robot hand. These experiments suggest the effectiveness and task relevance of the proposed grasp quality measure.
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paper_title: Sensing and End-Effector for a Robotic Tomato Harvester

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Fresh produce is important for long-term space missions. It provides valuable nutritional ::: needs and psychological boost for mission crews. Labor requirements to grow and harvest the crops, ::: however, must be reduced through automation to allow the crew to perform other tasks. A robotic ::: tomato harvester was developed for continuous, selective picking of mature tomatoes. The goal of ::: this project was to develop a sensing unit and a robotic hand unit that could be integrated with a ::: commercial robotic manipulator for the automated tomato harvesting task. Image processing ::: algorithms were developed to determine sizes and locations of mature tomatoes including the ones ::: that are partially occluded by leaves and/or branches. An end-effector subsystem, including a fourfinger ::: prosthetic hand and an embedded hand controller, was designed and assembled for the ::: tomato picking, holding and placing task. Improvement of a previously designed robotic hand ::: resulted in a 50% weight reduction. The sensing and picking capability of the units has been ::: demonstrated in laboratory and commercial greenhouse environments. Success rates of tomato fruit ::: sensing and picking were better than 95% and 85%, respectively.
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paper_title: On the Influence of Contact Geometry on Grasp Stability

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This paper demonstrates that the predicted grasp stabilityis highly sensitive to only small changes in thecharacter of the con- tact forces. The contribution of the geometry and stiffnessat the contact points to the grasp stability is investigated by a pl anar grasp with three contact points. Limit cases of zero and infin ite contact curvatures, and finite to infinite contact stiffnesses are considered. The stability is predicted based on the approac h of Howard and Kumar (1), and verified with multibody dynamic simulations. For rigid objects and fingers with only normal c tact stiffness, the grasp stability is dominated by the cont act ge- ometry, whereas the local contact stiffness and preload hav e a minor effect. Furthermore, grasps with pointed finger tips a re more likely to be stable than grasps with flat finger tips.
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paper_title: Grasp-state plane analysis of two-phalanx underactuated fingers

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Abstract This paper presents a new technique to analyze the grasp stability of two-phalanx underactuated fingers of general architecture using a grasp-state plane approach. Similarly to the state plane analysis for dynamical systems, a grasp-state plane technique is very elegant and efficient to study the grasp stability of two-phalanx underactuated fingers. The concept of underactuation in robotic fingers—with fewer actuators than degrees of freedom—allows the hand to adjust itself to an irregularly shaped object without complex control strategy and numerous sensors. However, in some configurations, the force distribution of an underactuated finger can degenerate, i.e. the finger can no longer apply forces on the object. This situation leads in some cases to the ejection of the object from the hand. This paper focuses on two-phalanx fingers and studies their ability to seize objects with a secure grasp, considering practical issues on the grasp, namely the local geometry of the contact, the influence of design parameters and friction. A grasp-state representation which allows to accurately visualize the contact state trajectory as well as equilibrium and unstable situations is presented.
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paper_title: Heavy material handling manipulator for agricultural robot

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This paper presents a manipulator which is able to handle heavy materials for agricultural applications. The characteristics of agricultural operation are discussed and extracted. As the manipulator for handling heavy materials is analyzed using kinematic indices, the parallel type manipulator is shown to be superior to the other manipulators (i.e. the polar coordinate type, articulated type and cylindrical coordinate type manipulators). A parallel type manipulator has therefore been designed and developed. The robotic harvesting experiment was carried out using the parallel type manipulator in a watermelon field.
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paper_title: Control of Grasp Stability When Humans Lift Objects With Different Surface Curvatures

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Jenmalm, Per, Antony W. Goodwin, and Roland S. Johansson. Control of grasp stability when humans lift objects with different surface curvatures. J. Neurophysiol. 79: 1643–1652, 1998. In previous investigations of the control of grasp stability, humans manipulated test objects with flat grasp surfaces. The surfaces of most objects that we handle in everyday activities, however, are curved. In the present study, we examined the influence of surface curvature on the fingertip forces used when humans lifted and held objects of various weights. Subjects grasped the test object between the thumb and the index finger. The matching pair of grasped surfaces were spherically curved with one of six different curvatures (concave with radius 20 or 40 mm; flat; convex with radius 20, 10, or 5 mm) and the object had one of five different weights ranging from 168 to 705 g. The grip force used by subjects (force along the axis between the 2 grasped surfaces) increased with increasing weight of the object but was modified inconsistently and incompletely by surface curvature. Similarly, the duration and rate of force generation, when the grip and load forces increased isometrically in the load phase before object lift-off, were not influenced by surface curvature. In contrast, surface curvature did affect the minimum grip forces required to prevent frictional slips (the slip force). The slip force was smaller for larger curvatures (both concave and convex) than for flatter surfaces. Therefore the force safety margin against slips (difference between the employed grip force and the slip force) was higher for the higher curvatures. We conclude that surface curvature has little influence on grip force regulation during this type of manipulation; the moderate changes in slip force resulting from changes in curvature are not fully compensated for by changes in grip force.
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paper_title: A Multi-Sensory End-Effector for Spherical Fruit Harvesting Robot

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An end-effector for spherical fruit harvesting robot was developed. This end-effector is a multi-sensory one that is universal for spherical fruit such as tomatoes, apples and citrus. It performs fruit singulation with a vacuum suction pad device, fruit gripping and peduncle locating with a two-finger (an upper finger and a lower finger) gripper and peduncle cutting with a laser cutting device. In order to percept sufficient information of the internal state, harvesting object and environment, different types of sensors are configured, including a vacuum pressure sensor, distance sensors, proximity sensors and force sensors. An open architecture of control system based on IL+DSP is adopted, which is more open, flexible, universal and lighter to be more suitable for a mobile harvesting robot and end-effector.
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paper_title: Grasp stability analysis considering the curvatures at contact points

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Proposes a method for analyzing the stability of grasps. The characteristic points in this paper are to consider the curvature of both hand and object at contact points and the grasp with friction and frictionless contact. From this analysis, it is shown that the grasp using round fingers is more stable than using sharp fingers. Moreover, we establish the condition on the finger's stiffness to stabilize the grasp with friction. It is proved that the required stiffness of fingers are decreased by considering the curvature. The stability analysis is greatly simplified by using potential energy of the grasp system and is of practical use.
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paper_title: Robot Gripper Analysis: Finite Element Modeling and Optimization

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A procedure for analysis and optimization of robot gripper designs has been developed. The procedure was applied to the specific problem of optimizing the weight of two different robot grippers for harvesting melons. The initial designs were modeled and analyzed using the finite element method to determine the critical static stresses. In one design, the stresses obtained were compared to analytical results and the finite element results were within 7% on average, which is sufficient for this preliminary design. In the second design, the trend and location of the maximum stresses agreed with a previously published photoelasticity study. The initial designs were then improved by applying optimization techniques to minimize the weight of the gripper while ensuring that the gripper was strong enough to withstand the load of the melon. The final designs were significantly lighter than the initial ones which reduce the required inertia forces. Based on the results of the proposed approach, an optimized gripper could then be constructed.
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paper_title: Contact stability for two-fingered grasps

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Two types of grasp stability, spatial grasp stability and contact grasp stability, each with a different concept of the state of a grasp, are distinguished and characterized. Examples are presented to show that spatial stability cannot capture certain intuitive concepts of grasp stability and hence that any full understanding of grasp stability must include contact stability. A model of how the positions of the points of contact evolve in time on the surface of a grasped object in the absence of any external force or active feedback is then derived. From the model, a general measure of the contact stability of any two-fingered grasp is obtained. Finally, the consequences of this stability measure and a related measure of contact manipulability on strategies for grasp selection are discussed. >
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paper_title: Internal forces and stability in multi-finger grasps

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Abstract This paper deals with the rotational stability of a rigid body under constant contact forces. For this system, the stiffness tensor is derived, and its basic properties are analyzed. For the gravity-induced stiffness, one condition for stability, formulated in terms of geometric and gravity centers, is obtained. The internal forces are introduced with the use of a virtual linkage model. Within this representation, two conditions for stability under internal force loading are formulated in an analytical form. The conditions obtained are applied to the synthesis of a three-fingered grasp.
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paper_title: Vision-based three-finger grasp synthesis constrained by hand geometry

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Abstract This paper addresses the problem of designing a practical system able to grasp real objects with a three-fingered robot hand. A general approach for synthesizing two- and three-finger grasps on planar unknown objects is presented. Visual perception is used to reduce the uncertainty and to obtain relevant information about the objects. We focus on non-modeled planar extruded objects, which can represent many real-world objects. In addition, particular mechanical constraints of the robot hand are considered. First, a vision processing module that extracts from object images the relevant information for the grasp synthesis is developed. This is completed with a set of algorithms for synthesizing two- and three-finger grasps taking into account force-closure and contact stability conditions, with a low computational effort. Finally, a procedure for constraining these results to the kinematics of the particular hand, is also developed. In addition, a set of heuristic metrics for assessing the quality of the computed grasps is described. All these components are integrated in a complete system. Experimental results using the Barrett hand are shown and discussed.
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paper_title: Manipulation of polygonal objects with two wheeled-tip fingers: Planning in the presence of contact position error

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This paper addresses the planning problem of object manipulation using wheeled-tip robots considering the wheel-object contact positioning error. The term wheeled-tip refers to a new mechanism that incorporates active wheels at robot's fingertips and allows the grasp contact-point to move along the object's surface. The benefits of unlimited rolling contact is achieved at the cost of contact positioning error that may cause the manipulation to fail. We propose a probabilistic based algorithm for robot motion planning that in addition to being collision free, guarantees the stability of the grasp throughout the planned path. To do so, first we introduce an algorithm that ensures the kinematical stability of the grasp during manipulation by respecting the force closure constraint. Further we extend the algorithm to address the practical uncertainties involved in the position of wheel-object contact points. The proposed algorithms can be employed for manipulators with limited rolling contacts, as well. The algorithms have been tested and the results prove that the planned path can be trusted in uncertain situations.
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paper_title: Optimal Thresholding for the Automatic Recognition of Apple Fruits

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The aging and the decreasing number of farm workers in Japan have been a ::: potential problem. That is why research on the automation of agricultural operations is ::: conducted in recent years. One of these operations is the harvesting of fruit trees such as the ::: apples. A robotic hand that could harvest the apple fruit similar to the human picker has been ::: developed, however the visual guidance of the developed hand has not yet been made. In this ::: paper, a machine vision system that would guide the robotic harvesting hand was studied. The ::: machine vision system consisted of a digital video camera and a personal computer. ::: Images of a Fuji apple tree were analyzed and histograms of its luminance and color difference ::: of red were developed. The threshold for segmentation of the images to recognize the fruit ::: portion was estimated from the histograms using the optimal thresholding method. The ::: estimated threshold effectively recognized the fruit portion. The threshold calculated from the ::: luminance histogram using the optimal thresholding method was not effective in recognizing the ::: Fuji apple while the threshold selected from the color difference of red histogram was effective ::: in recognizing the Fuji apple.
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paper_title: Recognition and cutting system of sweet pepper for picking robot in greenhouse horticulture

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This paper describes recognition and cutting system of sweet peppers for picking robots in greenhouse horticulture. This picking robot has an image processing system with a parallel stereovision, a camera positioning system to follow the sweet pepper by visual feedback control, and a cutting device. A prototype robot system has been made and is introduced. Experiments of the prototype prove that performance of the cutting system depends on recognition of fruits of sweet peppers. Consequently, the robot has ability for picking sweet peppers.
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paper_title: A Machine Vision for Tomato Cluster Harvesting Robot

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Dutch style greenhouses for tomato production are recently becoming popular in many countries while fruit cluster harvesting is also becoming popular in the Netherland and other countries where the Dutch system is introduced due to higher workability and fruit freshness. In the large scale Dutch production system, it is desirable to replace human operations into automated machines. In this paper, a machine vision system for a tomato fruit cluster harvesting robot is described. This machine vision system consisted of two identical color TV cameras (VGA class), four lighting devices with PL filters, and two image capture boards. Two images were acquired at a time and RGB color component images were converted into HSI images. Using colors on the HSI images, main stems, peduncles, and fruits were discriminate and an end-effector grasping point on the main stem was recognized based on physical properties of the tomato plant. Since difficulty to recognize the grasping point depended on exposure of plant parts and on robot access angle, acquired images were classified into three groups; Group A was images in which the fruit cluster, the stem, and the peduncle were isolated from the other plant parts. Group B was images in which they existed with adjacent plant parts. Group C was images in which some of them were occluded. From an experiment, results showed that 73% of grasping points on main stems were successfully recognized excluding Group C which was not able to be recognized also by human eyes.
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paper_title: Improvement of the Ability to Recognize Sweet Peppers for Picking Robot in Greenhouse Horticulture

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This paper describes improvement of the ability to recognize sweet peppers for picking robot in greenhouse horticulture. A prototype of the picking robot for sweet peppers has been manufactured. This robot has an image processing system, a camera positioning system, and a cutting device. However the ability to recognize sweet peppers was low, the picking ability was also low. The color of fruits of sweet peppers is almost same color of leaves of it. For identifying a fruit from leaves, this system needs the lighting system. At first we used the fluorescent lamp on the lighting system. In this system, it was possible to identify only fruits in the condition of mixed fruits and leaves. However, if the fruits overlapping with several other fruits, the shapes of these fruits did not exactly recognize, and it is possible to be different the two fruits that are recognized by right and left camera. In this case, because it cannot to exactly measure by stereovision system, the picking ability became low. So we use the new lighting system with LED. In the result of experiments, this CDD lighting system improves the ability to recognize the sweet peppers.
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paper_title: Fruit harvesting robots in Japan

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Abstract We have developed harvesting robots for tomato /1/, petty-tomato, cucumber /2/ and grape /3/ in Japan. These robots mainly consist of manipulators, end-effectors, visual sensors and traveling devices. These mechanisms of the robot components were developed based on the physical properties of the work objects. The robots must work automatically by themselves in greenhouses or fields, since we are considering for one operator to tend several robots in the production system. The system is modeled after Japanese agriculture which is commonly seen to produce many kinds of crops in greenhouses and in many small fields intensively. Bioproduction in space is somewhat similar to the agricultural system in Japan, because few operators have to work in a small space. Employing robots for bioproduction in space is considered desirable in near future. The following is a description of the harvesting robots.
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paper_title: Measurement of 3-D Locations of Ripe Tomato by Binocular Stereo Vision for Tomato Harvesting

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A measurement of 3-D locations of ripe tomato by binocular stereo vision was developed for tomato harvesting in greenhouse. In this method, a pair of stereo images was obtained by stereo cameras, and transformed to grey-scale images. According to the grey correlation, corresponding points of the stereo images were searched, and a depth image was obtained by calculating distances between tomatoes and stereo cameras based on triangulation principle. The center of tomato was extracted by distinguishing the tomato from background with image processing. The 3-D locations of ripe tomato were obtained by comparing coordinate values of the center of tomato with the depth image. The error of depth was ranged within ±20 mm when distance was less than 1000 mm.
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paper_title: Current Developments in Automated Citrus Harvesting

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The area of intelligent automated citrus harvesting has become a renewed area of research ::: in recent years. The renewed interest is a result of increased economic demand for better solutions ::: for selective automated citrus harvesting than are currently available by purely mechanical ::: harvesters. Throughout this paper the main challenges facing intelligent automated citrus harvesting ::: are addressed: fruit detection and robotic harvesting. The area of fruit detection is discussed, and ::: incorporates the important properties of citrus that can be used for detection. Robotic harvesting is ::: covered, and involves the discussion of the main mechanical design needs as well as the use of ::: visual servoing for the control of the robotic harvester. A description of our proposed intelligent citrus ::: harvesting system as well as our current prototype is presented.
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paper_title: Image analysis for agricultural processes: a review of potential opportunities

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Abstract Image analysis and interpretation by computers has many potential applications for guidingor controlling agricultural processes. However, research from industrial applications cannot be applied directly to agriculture because of problems such as the biological variability of objects or workpieces, and difficulty in interpreting unstructured environments. This paper describes the process of image analysis, its application to agriculture, and thegeneric problems particularly relevant to agricultural processes. Priority areas for further research are suggested. Ways of including knowledge in algorithms should be studied. Specific applications should also be studied including the practical problems of integrating image processing into larger systems.
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paper_title: Machine Vision Algorithm for Robots to Harvest Strawberries in Tabletop Culture Greenhouses

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A strawberry harvesting robot consisting of a four DOF manipulator, an end-effector with suction pad, a three camera vision system and a rail type traveling device was developed as a trial to conduct experiments in a tabletop culture greenhouse. In order to harvest the strawberries with curved or inclined peduncles, a wrist joint which can rotate 15 degrees to the left or right from its base position was added. On the algorithm side, peduncle inclination angle was measured by the center camera. Harvesting experiments show that it was possible to precisely harvest more than 75% of fruits which were not occluded by other fruits with the developed robot. Experimental data also show that peduncle length, color and inclination pattern change with the seasons. Complex situations often exist in the real field conditions such as limited visibility of back end strawberries, occluded fruits, obstructions and complex peduncle patterns. Further studies are desirable to automate the harvesting task using a robot.
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paper_title: THE FLORIDA ROBOTIC GROVE-LAB

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ABSTRACT A mobile grove-lab was developed to study the use of robotic technology for picking oranges under actual production conditions. The design and operation of the citms picking robot developed for this facility is described. The sensor system developed to identify and locate fruit in real-time and the state network programming technique used to develop a task-level control program for the citrus picking robot are discussed. The suitability of the vision system and state network programming technique for real-time, vision-servo robotic picking is demonstrated. It was concluded that the technical and economic practicality of robotic citrus harvesting can only be demonstrated with an operational multiple-arm harvesting system. Multiple usage of robotic harvesting equipment and acquisition of detailed production data by a robotic harvester were identified as intangible benefits of robotic harvesting which should encourage the commercial development of a multiple-arm machine.
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paper_title: Collision-free Motion Planning for a Cucumber Picking Robot

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One of the most challenging aspects of the development, at the Institute of Agricultural and Environmental Engineering (IMAG B.V.), of an automatic harvesting machine for cucumbers was to achieve a fast and accurate eye-hand co-ordination during the picking operation. This paper presents a procedure developed for the cucumber harvesting robot to pursue this objective. The procedure contains two main components. First of all acquisition of sensory information about the working environment of the robot and, secondly, a program to generate collision-free manipulator motions to direct the end-effector to and from the cucumber. This paper elaborates on the latter. Collision-free manipulator motions were generated with a so-called path search algorithm. In this research the A*-search algorithm was used. With some numerical examples the search procedure is illustrated and analysed in view of application to cucumber harvesting. It is concluded that collision-free motions can be calculated for the seven degrees-of-freedom manipulator used in the cucumber picking device. The A*-search algorithm is easy to implement and robust. This algorithm either produces a solution or stops when a solution cannot be found. This favourable property, however, makes the algorithm prohibitively slow. The results showed that the algorithm does not include much intelligence in the search procedure. It is concluded that to meet the required 10 s for a single harvest cycle, further research is needed to find fast algorithms that produce solutions using as much information about the particular structure of the problem as possible and give a clear message if such a solution can not be found
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paper_title: Automatic recognition vision system guided for apple harvesting robot

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In apple harvesting robot, the first key part is the machine vision system, which is used to recognize and locate the apples. In this paper, the procedure on how to develop an automatic recognition vision system guided for apple harvesting robot, is proposed. We first use a color charge coupled device camera to capture apple images, and then utilize an industrial computer to process images for recognising fruit. Meanwhile, the vector median filter is applied to remove the color images noise of apple, and images segmentation method based on region growing and color feature is investigated. After that the color feature and shape feature of image are extract, a new classification algorithm based on support vector machine for apple recognition is introduced to improve recognition accuracy and efficiency. Finally, these procedures proposed have been tested on apple harvesting robot under natural conditions in September 2009, and showed a recognition success rate of approximately 89% and average recognition time of 352ms.
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paper_title: Computer vision for fruit harvesting robots – state of the art and challenges ahead

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Despite extensive research conducted in machine vision for harvesting robots, practical success in this field of agrobotics is still limited. This article presents a comprehensive review of classical and state-of-the-art machine vision solutions employed in such systems, with special emphasis on the visual cues and machine vision algorithms used. We discuss the advantages and limitations of each approach and we examine these capacities in light of the challenges ahead. We conclude with suggested directions from the general computer vision literature which could assist our research community meet these challenges and bring us closer to the goal of practical selective fruit harvesting robots.
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paper_title: Measurement of 3-D Locations of Fruit by Binocular Stereo Vision for Apple Harvesting in an Orchard

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This paper describes the results of measurement of 3-D locations of fruit by binocular stereo vision ::: for apple harvesting in an orchard. In the method of image processing, a 3-D space is divided into a number of ::: cross sections at an interval based on disparity that is calculated from a gaze distance, and is reconstructed by ::: integrating central composite images owing to stereo pairs. Three measures to restrict false images were ::: proposed: (1) a set of narrow searching range values, (2) comparison of an amount of color featured on the ::: half side in a common area, and (3) the central composition of the half side. Experiments with a trial stereo ::: system were conducted on ripe apples in red (search distance ranging from 1.5m to 5.5m) and in yellow-green ::: (search range of 2m to 4m) in an orchard. The results showed that two measures of (1) and (3) were effective, ::: whereas the other was effective if there was little influence of background color similar to that of the objects. ::: The rate of fruit discrimination was about 90% or higher in the images with 20 to 30 red fruits, and from 65% to ::: 70% in images dense with red fruit and in the images of yellow-green apples. The errors of distance ::: measurement were about ±5%.
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paper_title: Robotic melon harvesting

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Intelligent sensing, planning, and control of a prototype robotic melon harvester is described. The robot consists of a Cartesian manipulator mounted on a mobile platform pulled by a tractor. Black and white image processing is used to detect and locate the melons. Incorporation of knowledge-based rules adapted to the specific melon variety reduces false detections. Task, motion and trajectory planning algorithms and their integration are described. The intelligent control system consists of a distributed blackboard system with autonomous modules for sensing, planning and control. Procedures for evaluating performance of the robot performing in an unstructured and changing environment are described. The robot was tested in the field on two different melon cultivars during two different seasons. Over 85% of the fruit were successfully detected and picked.
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paper_title: Apple Fruits Recognition Under Natural Luminance Using Machine Vision

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In this study, edge detection and combination of color and shape analyses was utilized to segment images of red apples obtained under natural lighting. Thirty images were acquired from an orchard in order to find an apple in each image and to determine its location. Two algorithms (edge detection-based and color- shape based) were developed to process the images. They were filtered, converted to binary images, and noise- reduced. Edge detection based algorithm was not successful, while color-shape based algorithm could detect apple fruits in 83.33% of images.
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paper_title: DETERMINING THE 3-D LOCATION OF THE APPLE FRUIT DURING HARVEST

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The objective of this research is to develop an apple harvesting robot. One of the engineering challenges is the real-time determination of the 3-D location of the fruit. In this paper, the development of a sensor to determine the 3-D location of Fuji apples is discussed. Two methods were considered in determining the 3-D location of the fruit: machine vision system and laser ranging system. Both of these systems would be mounted on the end effector. The machine vision system consisted of the color CCD video camera and the PC for the image processing. The distance from end effector to fruit can be determined using machine vision only, the differential object size method and the binocular stereo image method. However, the laser ranging system was considered because distance measurement using machine vision only is computationally expensive and time consuming. In the laser ranging system, this system needs the aid of the machine vision system to locate the two-dimensional location of the fruit. Then the laser ranging system determines the distance from the end effector to the fruit. The result obtained from this measurement system will be used as input to guide the motion of the manipulator.
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paper_title: Detection and three-dimensional localization by stereoscopic visual sensor and its application to a robot for picking asparagus

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Abstract This paper describes a three-dimensional localization process used on an agricultural robot designed to pick white asparagus. The system uses two cameras (CCD and Newvicon). Thanks to diascopic lighting, the images can easily be binarized. The threshold of digitalization is determined automatically by the system. A statistical study of the different shapes of asparagus tips allowed us to determine certain discriminating parameters to detect the tips as they appear on the silhouette of the mound of earth. The localization is done stereometrically with two cameras. As the robot carrying the system moves, the images are altered and decision criteria modified. A study of the images from mobile objects produced by both tube and CCD cameras was carried out. A simulation of this phenomenon has been done to determine the modifications concerning object shapes, thresholding levels and decision parameters as a function of robot speed.
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paper_title: Applied machine vision of plants: a review with implications for field deployment in automated farming operations

paper_content:

Automated visual assessment of plant condition, specifically foliage wilting, reflectance and growth parameters, using machine vision has potential use as input for real-time variable-rate irrigation and fertigation systems in precision agriculture. This paper reviews the research literature for both outdoor and indoor applications of machine vision of plants, which reveals that different environments necessitate varying levels of complexity in both apparatus and nature of plant measurement which can be achieved. Deployment of systems to the field environment in precision agriculture applications presents the challenge of overcoming image variation caused by the diurnal and seasonal variation of sunlight. From the literature reviewed, it is argued that augmenting a monocular RGB vision system with additional sensing techniques potentially reduces image analysis complexity while enhancing system robustness to environmental variables. Therefore, machine vision systems with a foundation in optical and lighting design may potentially expedite the transition from laboratory and research prototype to robust field tool.
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paper_title: A Harvesting Robot for Small Fruit in Bunches Based on 3-D Stereoscopic Vision

paper_content:

This paper describes the concept of a harvesting robotic system for small and delicate fruit ::: that may grow in bunches. The main component of the robot is the vision system that, unlike traditional ::: vision methods, is able to distinguish and locate each individual fruit in a bunch. It combines a passive and ::: an active 3-D reconstruction technique: stereoscopic vision and structured lighting. It is composed of two ::: stereoscopic cameras and a matrix of laser diodes, which is used to project a reticule of luminous spots ::: when a bunch is detected in order that the stereoscopic camera system can perform a 3-D reconstruction of ::: their position. A prototype of a harvesting robot based on it has been developed and tested with real ::: strawberry crops in hydroponic greenhouses. Some experimental results of these tests are included.
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paper_title: Design of an Agricultural Robot for Harvesting Melons

paper_content:

The performance of an agricultural robot has been evaluated through simulation to determine design parameters for a robotic melon harvester. Animated, visual simulation provided a powerful tool to initiate the evaluation of alternative designs. To quantify the many, closely-related design parameters, numerical simulation tools were developed and applied. Simulations using measured cantaloupe locations revealed the effect of design parameters (configuration, number of arms, and actuator speeds) on the average cycle time. Simulation results predicted that a Cartesian robot would perform faster than a cylindrical robot for the melon harvesting task. Activating two arms in tandem was the fastest configuration evaluated. Additional sets of melon locations were stochastically generated from distributions of the field data to determine performance for planting distances between 25 and 125 cm. The fastest cycle time was achieved for an experimental cultural practice that consisted of one plant on each half row in an alternating sequence with 125 cm planting distance. The performance of the robotic melon harvester was found to be highly dependent on the picking time, actuator speeds and planting distance.
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paper_title: Olive Fruits Recognition Using Neural Networks

paper_content:

A new method for olive fruit recognition is presented. Olive fruits size and weight are used for estimating the best harvesting moment of olive trees. Olive fruit recognition is performed by analyzing RGB images taken from olive trees. The harvesting decision comprehends two stages, the first stage focused on deciding whether or not the candidate identified in the picture corresponds to an olive fruit, and the second stage focused on olives overlapping in the pictures. The analyses required in these two stages are performed by implementing a neural networks solution approach.
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paper_title: Visual feedback guided robotic cherry tomato harvesting

paper_content:

Harvesting cherry tomatoes is more laborious than harvesting larger size tomatoes because of the high fruit density in every cluster. To save labor costs, robotic harvesting of cherry tomatoes has been studied in Japan. An effective vision algorithm, to detect positions of many small fruits, was developed for guidance of robotically harvested cherry tomatoes. A spectral reflectance in the visible region was identified and extracted to provide high contrast images for the fruit cluster identification. The 3-D position of each fruit cluster was determined using a binocular stereo vision technique. The robot harvested one fruit at a time and the position of the next target fruit was updated based on a newly acquired image and the latest manipulator position. The experimental results showed that this visual feedback control based harvesting method was effective, with a success rate of 70%.
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paper_title: Detection of Green Apples in Hyperspectral Images of Apple-Tree Foliage Using Machine Vision

paper_content:

It is important for orchard owners to be able to estimate the quantity of fruit on the trees at the various growth stages, because a tree that bears too many fruits will yield small fruits. Thus, if growers are interested in controlling the fruit size, knowing in advance that there are too many developing fruits will give them the opportunity to treat the tree. This study proposes a machine vision-based method of automating the yield estimation of apples on trees at different stages of their growth. Since one of the most difficult aspects of apple yield estimation is distinguishing between green varieties of apples or those that are green in the first stages of growth, and the green leaves that surround them, this investigation concentrates on estimating the yield of green varieties of apples. Hyperspectral imaging was used, because it is capable of giving a wealth of information both in the visible and the near-infrared (NIR) regions and thus offers the potential to provide useful results. A multistage algorithm was developed that uses several techniques, such as principle components analysis (PCA) and extraction and classification of homogenous objects (ECHO) for analyzing hyperspectral data, as well as machine vision techniques such as morphological operations, watershed, and blob analysis. The method developed was tested on images taken in a Golden Delicious apple orchard in the Golan Heights, Israel, in two sessions: one during the first stages of growth, and the second just before harvest. The overall correct detection rate was 88.1%, with an overall error rate of 14.1%.
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paper_title: Robust pixel-based classification of obstacles for robotic harvesting of sweet-pepper

paper_content:

Sweet-pepper plant parts should be distinguished to construct an obstacle map to plan collision-free motion for a harvesting manipulator. Objectives were to segment vegetation from the background; to segment non-vegetation objects; to construct a classifier robust to variation among scenes; and to classify vegetation primarily into soft (top of a leaf, bottom of leaf and petiole) and hard obstacles (stem and fruit) and secondarily into five plant parts: stem, top of a leaf, bottom of a leaf, fruit and petiole. A multi-spectral system with artificial lighting was developed to mitigate disturbances caused by natural lighting conditions. The background was successfully segmented from vegetation using a threshold in a near-infrared wavelength (>900nm). Non-vegetation objects occurring in the scene, including drippers, pots, sticks, construction elements and support wires, were removed using a threshold in the blue wavelength (447nm). Vegetation was classified, using a Classification and Regression Trees (CART) classifier trained with 46 pixel-based features. The Normalized Difference Index features were the strongest as selected by a Sequential Floating Forward Selection algorithm. A new robust-and-balanced accuracy performance measure P"R"o"b was introduced for CART pruning and feature selection. Use of P"R"o"b rendered the classifier more robust to variation among scenes because standard deviation among scenes reduced 59% for hard obstacles and 43% for soft obstacles compared with balanced accuracy. Two approaches were derived to classify vegetation: Approach A was based on hard vs. soft obstacle classification and Approach B was based on separability of classes. Approach A (P"R"o"b=58.9) performed slightly better than Approach B (P"R"o"b=56.1). For Approach A, mean true-positive detection rate (standard deviation) among scenes was 59.2 (7.1)% for hard obstacles, 91.5 (4.0)% for soft obstacles, 40.0 (12.4)% for stems, 78.7 (16.0)% for top of a leaf, 68.5 (11.4)% for bottom of a leaf, 54.5 (9.9)% for fruit and 49.5 (13.6)% for petiole. These results are insufficient to construct an accurate obstacle map and suggestions for improvements are described. Nevertheless, this is the first study that reports quantitative performance for classification of several plant parts under varying lighting conditions.
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paper_title: Spectral Imaging for Greenhouse Cucumber Fruit Detection Based on Binocular Stereovision

paper_content:

For a greenhouse cucumber-harvesting robot, two major challenges in the automated fruit-picking are to identify the target and to measure its position in the three dimensions. In this paper, a machine vision algorithm for recognition and location of cucumber fruits was presented. Firstly, a stereovision imaging system was established to capture monochrome near-infrared images, which are beneficial to deal with the similar-color segmentation problem in complex environment. Secondly, an image processing algorithm for cucumber recognition was proposed with the following steps: region partition according to 1-dimensional gray histogram distribution, adaptive threshold processing on divided local image, noise elimination using morphological analysis, and feature extraction with texture detection. Thirdly, the 3-D spatial position of fruit was calculated on the basis of standard triangulation model, meanwhile an auxiliary camera on the end-effector was introduced to improve cutting position. The experimental results from 120 cucumber image pairs taken in greenhouse showed that the proposed algorithm could detect fruit with a recognition rate of 86%. Also, the distance error of the grasping position(less than 8.6mm) and the maximum deviation of the cutting position (1.64mm in x-axis, 1.41mm in y-axis, 3.9mm in z-axis) were satisfied for robotic operation.
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paper_title: Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review

paper_content:

An overview is given of near infrared (NIR) spectroscopy for use in measuring quality attributes of horticultural produce. Different spectrophotometer designs and measurement principles are compared, and novel techniques, such as time and spatially resolved spectroscopy for the estimation of light absorption and scattering properties of vegetable tissue, as well as NIR multi- and hyperspectral imaging techniques are reviewed. Special attention is paid to recent developments in portable systems. Chemometrics is an essential part of NIR spectroscopy, and the available preprocessing and regression techniques, including nonlinear ones, such as kernel-based methods, are discussed. Robustness issues due to orchard and species effects and fluctuating temperatures are addressed. The problem of calibration transfer from one spectrophotometer to another is introduced, as well as techniques for calibration transfer. Most applications of NIR spectroscopy have focussed on the nondestructive measurement of soluble solids content of fruit where typically a root mean square error of prediction of 1° Brix can be achieved, but also other applications involving texture, dry matter, acidity or disorders of fruit and vegetables have been reported. Areas where more research is required are identified.
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paper_title: Robotic harvesting of Gerbera Jamesonii based on detection and three-dimensional modeling of cut flower pedicels

paper_content:

Within the present study, a system for the automated harvest of Gerbera jamesonii pedicels with the help of image analytic methods was developed. The study can be divided mainly into two parts: the development of algorithms for the identification of pedicels in digital images and the development of procedures for harvesting these pedicels with a robot. Images of plants were taken with a stereo camera system, which consisted of two high-resolution CCD-cameras with near-infrared filters. The plant was positioned on a rotatable working desk and images of eight different positions were shot. The developed image processing algorithm segmented the potential pedicel regions in the images, removed noise, differentiated overlapping pedicels by using different algorithms and combined the remaining regions to pedicel objects. From the data of both images and eight plant positions three-dimensional models of the pedicels were created by triangulation. The remaining parts of the plants were modeled in a simple fashion. The evaluated 3D model is used to calculate spatial coordinates for the applied robot control. For harvesting the pedicels, an industrial robot with six axes (plus an additional linear axis) was used. A pneumatic harvest grabber was developed, which harvested the pedicels by cutting them off. In order to guarantee the collision free path of the robot, a path planning module was integrated, which includes the three-dimensional model of the plant and the test facility. With the applied techniques it was possible to correctly detect all pedicels on about 72% of the images. Regarding the whole image series of the respective plant, all pedicels could be detected in at least one photographing position in 97% of all cases. In the harvest experiments 80% of all pedicels could be harvested. The harvest rates decreased with increasing numbers of pedicels on a plant. Therefore, 98% of the pedicels could be harvested of plants with one or two pedicels, but only 51% were harvested of plants with five or more pedicels. In horticultural practice, an identification system for evaluating the stage of maturity should be included. An implementation for harvesting pedicels of different species with similar basic characteristics is imaginable.
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paper_title: An Autonomous Robot for Harvesting Cucumbers in Greenhouses

paper_content:

This paper describes the concept of an autonomous robot for harvesting cucumbers in greenhouses. A description is given of the working environment of the robot and the logistics of harvesting. It is stated that for a 2 ha Dutch nursery, 4 harvesting robots and one docking station are needed during the peak season. Based on these preliminaries, the design specifications of the harvest robot are defined. The main requirement is that a single harvest operation may take at most 10 s. Then, the paper focuses on the individual hardware and software components of the robot. These include, the autonomous vehicle, the manipulator, the end-effector, the two computer vision systems for detection and 3D imaging of the fruit and the environment and, finally, a control scheme that generates collision-free motions for the manipulator during harvesting. The manipulator has seven degrees-of-freedom (DOF). This is sufficient for the harvesting task. The end-effector is designed such that it handles the soft fruit without loss of quality. The thermal cutting device included in the end-effector prevents the spreading of viruses through the greenhouse. The computer vision system is able to detect more than 95% of the cucumbers in a greenhouse. Using geometric models the ripeness of the cucumbers is determined. A motion planner based on the Aa-search algorithm assures collision-free eye-hand co-ordination. In autumn 2001 system integration took place and the harvesting robot was tested in a greenhouse. With a success rate of 80%, field tests confirmed the ability of the robot to pick cucumbers without human interference. On average the robot needed 45 s to pick one cucumber. Future research focuses on hardware and software solutions to improve the picking speed and accuracy of the eye-hand co-ordination of the robot.
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paper_title: Robot design and testing for greenhouse applications

paper_content:

The latest results of technology and research are increasingly used in agriculture, especially in intensive cultures that ensure remunerative returns. Most cultures in greenhouses are in this category where, despite the large use of technology, human operators still manually perform most operations on the crop although they are often highly repetitive and sometime even dangerous. This fact greatly impacts on the quality of the product, on the production costs and on collateral issues, such as pollution and safety. In this paper, the state of research in robotic automation in agriculture outlining the characteristics that robots should have to allow their profitable use is considered. A multi-purpose low-cost robot prototype, designed and built according to such characteristics, is then presented together with the results of some preliminary experimentation with it. Although more research is needed, the results prove to be promising and show some advantages that can be achieved with robotic automation. In particular, precision spraying and precision fertilisation applications have been developed and tested. Although the productivity of the prototype is quite low (in the range of 400–500 plant/h), experiments conducted continuously for several hours show that the robot can perform tasks unaffordable by human operators.
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paper_title: AN AUTONOMOUS ROBOT FOR DE-LEAFING CUCUMBER PLANTS GROWN IN A HIGH-WIRE CULTIVATION SYSTEM

paper_content:

The paper presents an autonomous robot for removing the leaves from cucumber plants grown in a high-wire cultivation system. Leaves at the lower end of the plants are removed because of their reduced vitality, their negligible contribution to canopy photosynthesis and their increased sensitivity for fungal diseases. Consuming 19% of the total labour input, leaf removal is considered by the growers and their staff as a tedious, repetitive and costly task. Automation alleviates their job and results in a significant cost reduction. Additionally, removal of the leaves results in an open structure of the canopy in which the fruit is clearly visible and accessible which is an advantage for automatic cucumber harvesting. The paper describes a functional model and results of a field test of the de-leafing robot. The field test confirmed the feasibility of the concept of the de-leafing robot.
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paper_title: Optimal manipulator design for a cucumber harvesting robot

paper_content:

This paper presents a procedure and the results of an optimal design of the kinematic structure of a manipulator to be used for autonomous cucumber harvesting in greenhouses. The design objective included the time needed to perform a collision-free motion from an initial position to the target position as well as a dexterity measure to allow for motion corrections in the neighborhood of the fruits. The optimisation problem was solved using the DIRECT algorithm implemented in the Tomlab package. A four link PPRR type manipulator was found to be most suitable. For cucumber harvesting four degrees-of-freedom, i.e. three translations and one rotation around the vertical axis, are sufficient. The PPRR manipulator described in this paper meets this requirement. Although computationally expensive, the methodology used in this research was found to be powerful and offered an objective way to evaluate and optimise the kinematic structure of a robot to be used for cucumber harvesting.
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paper_title: Recognition and cutting system of sweet pepper for picking robot in greenhouse horticulture

paper_content:

This paper describes recognition and cutting system of sweet peppers for picking robots in greenhouse horticulture. This picking robot has an image processing system with a parallel stereovision, a camera positioning system to follow the sweet pepper by visual feedback control, and a cutting device. A prototype robot system has been made and is introduced. Experiments of the prototype prove that performance of the cutting system depends on recognition of fruits of sweet peppers. Consequently, the robot has ability for picking sweet peppers.
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paper_title: Agricultural robot for radicchio harvesting

paper_content:

In the last few years, robotics has been increasingly adopted in agriculture to improve productivity and efficiency. This paper presents recent and current work at the Politecnico of Bari, in collaboration with the University of Lecce, in the field of agriculture robotics. A cost effective robotic arm is introduced for the harvesting of radicchio, which employs visual localization of the plants in the field. The proposed harvester is composed of a double four-bar linkage manipulator and a special gripper, which fulfills the requirement for a plant cut approximately 10 mm underground. Both manipulator and end-effector are pneumatically actuated, and the gripper works with flexible pneumatic muscles. The system employs computer vision to localize the plants in the field based on intelligent color filtering and morphological operations; we call this algorithm the radicchio visual localization RVL. Details are provided for the functional and executive design of the robotic arm and its control system. Experimental results are discussed; obtained with a prototype operating in a laboratory testbed showing the feasibility of the system in localizing and harvesting radicchio plants. The performance of the RVL is analyzed in terms of accuracy, robustness to noises, and variations in lighting, and is also validated in field
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paper_title: Ergonomics of manual harvesting

paper_content:

Abstract Manual harvesting has many advantages compared with the mechanical harvesting of most fruit crops. The most important advantage is visual image processing ability which enables workers rapidly to detect fruit suitable for harvest and direct their hand to the fruit selected for detachment. Lacking the necessary computer based image processing equipment, designers of mechanical harvesters have settled for mass removal approaches that typically results in more damage than normal when fruit is harvested individually. Although manual harvesting has the disadvantage of low capacity, it is expected that much of the world's fruit will continue to be harvested by hand for the foreseeable future. Several ergonomics principles that relate to manual harvesting are discussed. Methods for improving worker conditions and productivity are presented. Worker positioners increase productivity by 20 to 40% and enable use of sun shades, fans, conveyors and other devices that increase comfort and reduce fatique. Testing and training can yield substantial benefits from small inputs. Tests for visual acuity, colour sensitivity, strength, etc, can help managers assign tasks to the most suitable workers. Training programmes help workers to have a clear mental picture of acceptable fruit and encourage compliance with handling, safety and other procedures. Satisfaction of human drives such as thirst, hunger, thermal comfort and avoidance of pain results in long-range benefits.
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paper_title: Harvesting Robots for High-value Crops: State-of-the-art Review and Challenges Ahead

paper_content:

This review article analyzes state-of-the-art and future perspectives for harvesting robots in high-value crops. The objectives were to characterize the crop environment relevant for robotic harvesting, to perform a literature review on the state-of-the-art of harvesting robots using quantitative measures, and to reflect on the crop environment and literature review to formulate challenges and directions for future research and development. Harvesting robots were reviewed regarding the crop harvested in a production environment, performance indicators, design process techniques used, hardware design decisions, and algorithm characteristics. On average, localization success was 85%, detachment success was 75%, harvest success was 66%, fruit damage was 5%, peduncle damage was 45%, and cycle time was 33 s. A kiwi harvesting robot achieved the shortest cycle time of 1 s. Moreover, the performance of harvesting robots did not improve in the past three decades, and none of these 50 robots was commercialized. Four future challenges with R&D directions were identified to realize a positive trend in performance and to successfully implement harvesting robots in practice: 1 simplifying the task, 2 enhancing the robot, 3 defining requirements and measuring performance, and 4 considering additional requirements for successful implementation. This review article may provide new directions for future automation projects in high-value crops.
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paper_title: A setup of mobile robotic unit for fruit harvesting

paper_content:

The description of a mobile robotic unit for fruit harvesting was illustrated in this paper. The setup of the system was developed to harvest date palm fruit which is the most common fruit in Saudi Arabia. The system was based on readymade industrial robotic arm.
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paper_title: Fruit harvesting robots in Japan

paper_content:

Abstract We have developed harvesting robots for tomato /1/, petty-tomato, cucumber /2/ and grape /3/ in Japan. These robots mainly consist of manipulators, end-effectors, visual sensors and traveling devices. These mechanisms of the robot components were developed based on the physical properties of the work objects. The robots must work automatically by themselves in greenhouses or fields, since we are considering for one operator to tend several robots in the production system. The system is modeled after Japanese agriculture which is commonly seen to produce many kinds of crops in greenhouses and in many small fields intensively. Bioproduction in space is somewhat similar to the agricultural system in Japan, because few operators have to work in a small space. Employing robots for bioproduction in space is considered desirable in near future. The following is a description of the harvesting robots.
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paper_title: Status of citrus harvesting in Florida

paper_content:

Abstract Florida citrus production peaked at 11·2 Mt prior to several damaging freezes of the early 1980s. Currently, production is seven Mt, slowly increasing, and approximately 83% is utilized for processing purposes. The picking of citrus is still a manual task and currently requires 20 000 labourers. The labour supply appears adequate with a reasonably good profit margin above harvesting costs. Although 30 years of research and development have not yielded a feasible alternative to manual picking, considerable technology has been developed to evaluate the merits of various approaches. Picking aids have increased picker productivity, but their economic justification under Florida labour conditions continues to be questionable. Mass removal mechanical systems could only compete on a small scale to traditional citrus harvesting methods. The freezes of the early 1980s eliminated many of the old, larger producing trees in the north central area of the state. New plantings are being spaced closer together to achieve high yields in hedgerows at an early age. Hand harvesters generally dislike hedgerows because across-row movement with ladders and containers is more difficult. Also, mechanical placement and retrieval of fruit containers in the rows are difficult. The application of robotic principles favours hedgerows because positioning of a robotic arm would be much simpler than with individual trees. A robotic arm under development in Florida has demonstrated a picking rate of one fruit every five seconds from the outer canopy. Research is underway to develop smaller and more productive hedgerow trees which would be easier to harvest by hand or machine.
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paper_title: Current Developments in Automated Citrus Harvesting

paper_content:

The area of intelligent automated citrus harvesting has become a renewed area of research ::: in recent years. The renewed interest is a result of increased economic demand for better solutions ::: for selective automated citrus harvesting than are currently available by purely mechanical ::: harvesters. Throughout this paper the main challenges facing intelligent automated citrus harvesting ::: are addressed: fruit detection and robotic harvesting. The area of fruit detection is discussed, and ::: incorporates the important properties of citrus that can be used for detection. Robotic harvesting is ::: covered, and involves the discussion of the main mechanical design needs as well as the use of ::: visual servoing for the control of the robotic harvester. A description of our proposed intelligent citrus ::: harvesting system as well as our current prototype is presented.
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paper_title: Design of an autonomous agricultural robot

paper_content:

This paper presents a state-of-the-art review in the development of autonomous agricultural robots including guidance systems, greenhouse autonomous systems and fruit-harvesting robots. A general concept for a field crops robotic machine to selectively harvest easily bruised fruit and vegetables is designed. Future trends that must be pursued in order to make robots a viable option for agricultural operations are focused upon.A prototype machine which includes part of this design has been implemented for melon harvesting. The machine consists of a Cartesian manipulator mounted on a mobile chassis pulled by a tractor. Two vision sensors are used to locate the fruit and guide the robotic arm toward it. A gripper grasps the melon and detaches it from the vine. The real-time control hardware architecture consists of a blackboard system, with autonomous modules for sensing, planning and control connected through a PC bus. Approximately 85% of the fruit are successfully located and harvested.
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paper_title: Design and implementation of an aided fruit‐harvesting robot (Agribot)

paper_content:

This work presents a robot prototype designed and built for a new aided fruit‐harvesting strategy in highly unstructured environments, involving human‐machine task distribution. The operator drives the robotic harvester and performs the detection of fruits by means of a laser range‐finder, the computer performs the precise location of the fruits, computes adequate picking sequences and controls the motion of all the mechanical components (picking arm and gripper‐cutter). Throughout this work, the specific design of every module of the robotized fruit harvester is presented. The harvester has been built and laboratory tests with artificial trees were conducted to check range‐finder’s localization accuracy and dependence on external conditions, harvesting arm’s velocity, positioning accuracy and repeatability; and gripper‐cutter performance. Results show excellent range‐finder and harvesting arm operation, while a bottleneck is detected in gripper‐cutter performance. Some figures showing overall performance are given.
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paper_title: Review on fruit harvesting method for potential use of automatic fruit harvesting systems

paper_content:

In horticultural industry, conventional harvesting is done by ‘handpicking’ methods to remove hundreds of fruits such as citrus fruits in random spatial locations on the individual fruit trees. It is well known that harvesting fruits in a large scale is still inefficient and not cost effective. To solve this challenging task, mechanical harvesting systems have been investigated and practiced to enhance profitability and efficiency of horticultural businesses. However they often damage fruits in the harvesting process. Development of efficient fruit removal methods are required to maintain the fruits quality. This paper reviews fruit harvesting systems from purely mechanical based systems in which operator involvement is still required, to automatic robotic harvesting systems which require minimal or no human intervention in their operation. The researches on machine vision system methodologies used in the automatic detection, inspection and the location of fruits for harvesting are also included. The review is focused on the citrus fruits due to the fact that the research on citrus fruit harvesting mechanism is a bit more advanced than others. Major issues are addressed in the camera sensor and filter designs and image segmentation methods used to identify the fruits within the image. From this review, the major research issues are addressed as future research directions.
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paper_title: Development of an autonomous kiwifruit picking robot

paper_content:

The design concept and development status of an autonomous kiwifruit-picking robot is presented. The robot has an intelligent vision system that ensures that only “good” fruit is picked. The robot receives instruction by radio link and operates autonomously as it navigates through the orchard, picking fruit, unloading full bins of fruit, fetching empty bins and protecting the picked fruit from rain. The robot has four picking arms, each of which will pick one fruit per second. To extend the useful annual work period of the robot, it is envisaged that it will also be used to pollinate kiwifruit flowers.
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paper_title: On the future of automated selective asparagus harvesting technology

paper_content:

Abstract This paper assesses the current state and likely future developments of automated selective asparagus harvesting. It reports the current stage of a research and development programme, based on a selective asparagus harvester concept embodying electronic technology, that has been underway since 1989 at the Centre for Advanced Manufacturing and Industrial Automation (CAMIA) in the University of Wollongong. The findings of some seminal field trials of current asparagus harvesting technologies conducted in the US in May 1995 by the Washington Asparagus Commission in which the CAMIA machine was included, are discussed. The implications of these results are examined in regard to the future development of automated selective asparagus harvesters. It is concluded that further research and development is needed to balance the technological and financial factors before the economic viability of mechanised selective asparagus harvesting is assured. In this context, the CAMIA concept of a selective asparagus harvester employing electronic technology provides a sound platform for exploiting on-going rapid developments in control and sensors.
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paper_title: Robotic Harvesting System for Eggplants

paper_content:

The harvesting operation for eggplants is complicated and accounts for a little less than 40% of the total number of working hours. For automating the harvesting operation, an intelligent robot that can emulate the judgment of human labor is necessary. This study was conducted with a view to developing a robotic harvesting system that performs recognition, approach, and picking tasks. In order to accomplish these tasks, 3 essential components were developed. First, a machine vision algorithm combining a color segment operation and a vertical dividing operation was developed. The algorithm could detect the fruit even under different light conditions. Next, a visual feedback fuzzy control model to actuate a manipulator was designed. The control model enabled the manipulator end to approach the fruit from a distance of 300 mm. Furthermore, an end-effector composed of fruit-grasping mechanism, a size-judging mechanism, and a peduncle-cutting mechanism was developed. It produced enough force for grasping the fruit and cutting the tough peduncle. Finally, the 3 essential components were functionally combined, and a basic harvesting experiment was conducted in the laboratory to evaluate the performance of the system. The system showed a successful harvesting rate of 62.5%, although the end-effector cut the peduncle at a slightly higher position from the fruit base. The execution time for harvesting of an eggplant was 64.1 s.
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paper_title: An End-Effector for Robotic Removal of Citrus from the tree

paper_content:

ABSTRACT The design of a robotic end-effector for picking citrus fruit is presented and its performance evaluated. The end-effector utilized a rotating-lip mechanism to capture a fruit. Incorporated into the end-effector were a color CCD camera and an ultrasonic transducer for determining the location of a fruit in three dimensions. End-effector performance was assessed by quantifying its capture envelope, fruit removal success rate, and damage inflicted to fruit and tree. Capture envelop was determined with laboratory tests while success and damage rates were quantified through field trials. The end-effector successfully removed fruit in 69% of the pick attempts and caused damage on 37% of the pick attempts. It was concluded that the rotating-lip approach to citrus removal was appropriate but refinement of the end-effector was needed to improve its success rate and to reduce damage rates. KEYWORDS. Robotics, Harvesting, Citrus, End-Effector.
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paper_title: Autonomous Fruit Picking Machine: A Robotic Apple Harvester

paper_content:

This paper describes the construction and functionality of an Autonomous Fruit Picking Machine (AFPM) for robotic apple harvesting. The key element for the success of the AFPM is the integrated approach which combines state of the art industrial components with the newly designed flexible gripper. The gripper consist of a silicone funnel with a camera mounted inside. The proposed concepts guarantee adequate control of the autonomous fruit harvesting operation globally and of the fruit picking cycle particularly. Extensive experiments in the field validate the functionality of the AFPM.
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paper_title: Design of an Agricultural Robot for Harvesting Melons

paper_content:

The performance of an agricultural robot has been evaluated through simulation to determine design parameters for a robotic melon harvester. Animated, visual simulation provided a powerful tool to initiate the evaluation of alternative designs. To quantify the many, closely-related design parameters, numerical simulation tools were developed and applied. Simulations using measured cantaloupe locations revealed the effect of design parameters (configuration, number of arms, and actuator speeds) on the average cycle time. Simulation results predicted that a Cartesian robot would perform faster than a cylindrical robot for the melon harvesting task. Activating two arms in tandem was the fastest configuration evaluated. Additional sets of melon locations were stochastically generated from distributions of the field data to determine performance for planting distances between 25 and 125 cm. The fastest cycle time was achieved for an experimental cultural practice that consisted of one plant on each half row in an alternating sequence with 125 cm planting distance. The performance of the robotic melon harvester was found to be highly dependent on the picking time, actuator speeds and planting distance.
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paper_title: Design and Experiment of Intelligent Monorail Cucumbers Harvester System

paper_content:

Abstract. The cucumber with widespread planted area has a large market share. In order to achieve the requirement of high harvesting efficient under the existing planting patterns, the intelligent monorail cucumbers harvester system has been designed. The intelligent harvester which runs on the monorail is mainly composed with harvest box, monorail assembly bracket system, and control system. Its harvest box is placed on the hooks of the harvester. The way of image capturing with combination of infrared sensor and intelligent camera is feasible. The mature cucumbers can be distinguished by using gray transformation algorithm, trimming image edge algorithm, and locally maximal variance between-class threshold algorithm. The end-effector can be controlled to cut or avoid the cucumbers which hang on the hooks under the monorail during the falling vines. The results show that the average harvesting success rate is 97.28% when the running speed is 0.6m/s. It meets harvesting requirements, and has good prospects.
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paper_title: Robotic Harvesting of Rosa Damascena Using Stereoscopic Machine Vision

paper_content:

4 Abstract: In this paper, we propose a system for the automated harvest of Rosa Damascena by aid of computer vision techniques. Three dimensional positions of flowers are obtained by stereo vision technique. For harvesting flowers a four-DOF manipulator is used. Also, an end-effector is designed to harvest the flowers by cutting them. To analyze the stereoscopic error, a factorial experiment in the form of a completely randomized design with 2 factors was conducted. The first factor was the distance between cameras at the three levels of 5,10 and 20cm and the second factor was the distance between the camera and the flower at the four levels of 50,75,100 and 125cm. The analysis was done using Duncan's Multiple Range Test at the 1% level. We concluded that the increase in the distance between the cameras reduces the stereoscopic error, while the increase in the distance between the cameras and the flowers increases the error. Finally, the manipulator and the vision system were evaluated altogether. The best results were obtained when the relative distance between cameras was 100 mm. In this case, 82.22 percent of the flowers were successfully harvested.
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paper_title: Strawberry Harvesting Robot on Table-top Culture

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In this paper, it is reported that a robot was developed for harvesting strawberry grown on table top culture. The robot mainly consisted of a 4 DOF manipulator, a harvesting end-effector using sucking force and a visual sensor. As its manipulator, a Cartesian coordinate type was adopted and it was suspended under the planting bed of strawberry. The robot was capable of moving along the planting bed without a traveling device because one prismatic joint of the manipulator played the role of a traveling device. The end-effector could suck a fruit using a vacuum device and it could compensate detecting errors caused by the visual sensor. The visual sensor gave the robot two dimensional information based on an acquired image and fruit depth was calculated as an average value of previously harvested fruit depths obtained from end-effector positions when the robot actually harvested. The end-effector moved toward a target fruit based on the three dimensional position of the target fruit until the fruit was detected by three pairs of photo-interrupters on sucking head. After cutting the peduncle by using the robot's wrist joint, the fruits passed the tube and were transported to the tray. From the results of the harvesting experiments, it was observed that the robot could harvest all target fruits with no injury, and that depth measurement by a visual sensor was simplified because a distance between the robot and the fruits was kept an approximately constant by suspending the robot under the planting bed.
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paper_title: Automatic harvesting of asparagus: an application of robot vision to agriculture

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This work presents a system for the automatic selective harvesting of asparagus in open field being developed in the framework of the Italian National Project on Robotics. It is composed of a mobile robot, equipped with a suitable manipulator, and driven by a stereo-vision module. In this paper we discuss in detail the problems related to the vision module.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
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paper_title: Robotics and intelligent machines in agriculture

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-From the prehistoric times of the hunter/gatherers until the present, man has been the sole source of intelligence in his food production system. The combined factors of increased international competition in the agricultural sector, advances in computer technology, and the rapidly decreasing costs of new technology have now brought us to the time when the widespread application of intelligent machines in agriculture is imminent. Thus practical agricultural robots now seem possible. Agricultural robots and intelligent machines will increase and become commonplace in the developed countries during the next decade. The status of intelligent machines and robotics in agriculture as it stands at present is reviewed; i.e., where it is going and some of the obstacles that must be overcome.
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paper_title: Initial experiments in robotic mushroom harvesting

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Abstract The locating and picking performance of a robotic mushroom harvesting rig is assessed. The robot system has three main elements: a black and white vision system incorporating a mushroom locating image analysis algorithm, a computer-controlled Cartesian robot and a specialised mushroom picking end-effector. In 18 experiments, on 815 mushroom targets, 689 (84%) were located by the image analysis algorithm and 465 (57%) were picked successfully. Overlapped, small mushrooms and closely packed, touching mushrooms proved most difficult to pick using twist as the primary detachment method. The paper concludes that considerable improvements to picking performance could be achieved by using bend as the primary detachment method and by developing a suitable picking strategy to predict bend direction and picking order.
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paper_title: MECHANICAL HARVESTING SYSTEMS FOR THE FLORIDA CITRUS JUICE INDUSTRY

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Florida harvests 95% of its 245,000 ha of oranges for processing into ::: juice. Until recently, all fruit were hand harvested. The supply of workers is ::: decreasing and harvest cost is increasing. Harvest cost must be reduced about 50% ::: to effectively compete in free-trade markets. The Florida growers are funding a ::: Harvesting Program to develop new harvesting technologies. Eight mechanical ::: harvesting systems that are emerging for commercial use are described. About ::: 6,000 ha were mechanically harvested during the 2001-2002 season, and the total ::: should increase every year.
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paper_title: n End-Effector and Manipulator Control for Tomato Cluster Harvesting Robot

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An end-effector and a control method for tomato-cluster harvesting manipulator are proposed in this study. When fruit cluster harvesting is conducted, peduncle direction is necessary to cut, but is not easy to detect because peduncles are often occluded by leaves, stems and fruits. The end-effector needs to grasp the peduncle without its direction information. An end-effector which can surround main stem and can grasp and cut the peduncle by fingers was made as a trial. When a tomato cluster is transported into a container with the manipulator, both its transportation speed and vibration damping are required. Such a control problem is generally called a motion and vibration control (MOVIC). An input shaping method is one of the representative control methods for the MOVIC. It requires accurate natural frequencies of the manipulating target fruit cluster to damp the flexible vibration when the robot is accelerating the target. The tomato clusters, however, have individual variation with natural frequencies; hence, it is not easy to apply the input shaping method directly. To overcome this problem, identification method of natural frequency was combined with the input shaping method in the proposed method. This identification was based on real time sensing data from a machine vision and a force sensor and database of physical properties of the tomato clusters. Usefulness of the proposed method was verified through both numerical simulations and hardware experiments.
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paper_title: Design of an advanced prototype robot for white asparagus harvesting

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Agricultural workplaces are a prototypical example of unstructured and variant environments, offering a novel challenge to robotic research and automation. In this paper, a robot prototype is presented for white asparagus harvesting. White asparagus is a rather delicate vegetable with unique cultivation characteristics, which is exceptionally tiring and laborious to collect and requires specialized workers for harvesting. In this paper, we propose an integrated robotic system able to move in the field, identify white asparagus stems and collect them without damaging them. We highlight the design decisions for every module of the harvester and outline the overall architecture of the system.
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paper_title: Development of a cucumber leaf picking device for greenhouse production

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A leaf picking device for cucumbers was designed and evaluated. The picking device is manually operated but can be used as a picking tool for a robot. The device consisted of a picking rotor composed from knives and brushes, a motor and a vacuum cleaner. The performance of removal, cutting, torque and shredding was investigated in the laboratory experiments. In the greenhouse experiments, the performance of picking and cutting was investigated. The results were as follows: (1) the highest removal success rate was achieved at a rotation speed of 1000 min −1 , a rotor configuration of ‘two knives and two brushes’ and an insertion speed of 50 mm s −1 ; (2) in this mechanical setting, the percentage of the summation of the smooth cut surface of the leaf stalk and the smooth cut surface with small skin was 90%; (3) the required torque was 0.09–0.96 N m and the average particle size of the shredded leaves was 7.3–21.2 cm 2 ; (4) the percentages of area of the dropped particles to the average area of leaves was 10–16%; (5) the average execution time per leaf was 1.1–2.3 s.
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paper_title: Design and co-simulation for tomato harvesting robots

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A tomato harvesting robot consisting of a mobile vehicle, a manipulator, a vision system, an end-effector, a cutter and a control system is designed. Each module is described in detail. The manipulator is 4 DOF with one parallel linkage, which generate two directions' motion. The harvesting robot performed the harvesting task based on machine vision servo system. A personal computer working as the host computer conducted the manipulator, the end-effector and the cutter. The viability and validity of the tomato harvesting robot was preliminarily confirmed by co-simulation for the electromechanical system.
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paper_title: Robotics of Fruit Harvesting: A State-of-the-art Review

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Abstract Mechanization of the harvesting of fruits, and primarily of those that are destined for the fresh market, is highly desirable in many countries due to the decrease in seasonal labour availability. Some of the technology exists for harvesting fruit intended for processing, but its utilization for soft, fresh fruit is limited, because of the excessive mechanical damage to the fruit during mechanical harvesting. An alternative to the current mechanical harvesting systems, superior from the point of view of fruit quality, but far more ambitious, is automated fruit picking with a robotic system which emulates the human picker. The challenge of developing a cost-effective robotic system for fruit picking has been taken up by researchers at several places in the world. The major problems that have to be solved with a robotic picking system are recognizing and locating the fruit and detaching it according to prescribed criteria, without damaging either the fruit or the tree. In addition, the robotic system needs to be economically sound to warrant its use as an alternative method to hand picking. This paper reviews the work carried out during the past 10 years in several countries, in developing a robot for picking fruit. Its major objective is to focus on the technological progress made so far, point out the problems still to be solved, and outline the conditions, technological and socio-economic, under which the robotic method will be accepted.
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paper_title: A prototype of an orange picking robot: past history, the new robot and experimental results

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Purpose – To construct a commercial agricultural manipulation for fruit picking and handling without human intervention.Design/methodology/approach – Describes a research activity involving a totally autonomous robot for fruit picking and handling crates.Findings – Picking time for the robotic fruit picker at 8.7 s per orange is longer than the evaluated cited time of 6 s per orange.Research limitations/implications – The final system, recently tested, has not yet achieved a level of productivity capable of replacing human pickers. Further mechanical modifications and more robust and adaptive algorithms are needed to achieve a stronger robot system.Practical implications – Experimental results and new simulations look very promising.Originality/value – Will help to limit costs and guarantee a high degree of reliability.
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paper_title: THE FLORIDA ROBOTIC GROVE-LAB

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ABSTRACT A mobile grove-lab was developed to study the use of robotic technology for picking oranges under actual production conditions. The design and operation of the citms picking robot developed for this facility is described. The sensor system developed to identify and locate fruit in real-time and the state network programming technique used to develop a task-level control program for the citrus picking robot are discussed. The suitability of the vision system and state network programming technique for real-time, vision-servo robotic picking is demonstrated. It was concluded that the technical and economic practicality of robotic citrus harvesting can only be demonstrated with an operational multiple-arm harvesting system. Multiple usage of robotic harvesting equipment and acquisition of detailed production data by a robotic harvester were identified as intangible benefits of robotic harvesting which should encourage the commercial development of a multiple-arm machine.
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paper_title: Robotic manipulators in horticulture : a review

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Abstract This paper covers the use of jointed manipulators in handling biological materials within the horticultural industry. Potential applications are reviewed by looking at previous research work and the scope for future development based on economic as well as technical considerations. It is concluded that applications with long seasons are the most viable, with flexibility of use between tasks an important consideration for applications with short seasons. A general specification highlighting the differences between horticultural and manufacturing industry requirements has been derived and some engineering proposals put forward to meet it. The use of computer vision is thought to be the best choice of primary sensor system. A geometrical layout which allows the manipulator to approach the target along a "line of sight" is favoured, as it simplifies collision avoidance in an unstructured environment and might allow recalibration of manipulator position during extension. Pneumatic actuators are thought to offer many advantages over electric or hydraulic drives provided that adequate dynamic control can be achieved. It is concluded that the generic differences in specification between industrial and horticultural manipulators provide an opportunity to take a new approach in manipulator design. In order to provide the analytical tools necessary for this new approach further research is needed in the interrelated areas of actuator choice, geometrical configuration and control strategy.
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paper_title: New strawberry harvesting robot for elevated-trough culture

paper_content:

Feng Qingchun*, Wang Xiu, Zheng Wengang, Qiu Quan, Jiang Kai ::: (National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China) ::: ::: Abstract: In order to improve robotic harvesting and reduce production cost, a harvesting robot system for strawberry on the elevated-trough culture was designed. It was supposed to serve for sightseeing agriculture and technological education. Based on the sonar-camera sensor, an autonomous navigation system of the harvesting robot was built to move along the trough lines independently. The mature fruits were recognized according to the H (Hue) and S (Saturation) color feature and the picking-point were located by the binocular-vision unit. A nondestructive end-effector, used to suck the fruit, hold and cut the fruit-stem, was designed to prevent pericarp damage and disease infection. A joint-type industrial manipulator with six degrees-of-freedom (DOF) was utilized to carry the end-effector. The key points and time steps for the collision-free and rapid motion of manipulator were planned. Experimental results showed that all the 100 mature strawberry targets were recognized automatically in the harvesting test. The success harvesting rate was 86%, and the success harvesting operation cost 31.3 seconds on average, including a single harvest operation of 10 seconds. The average error for fruit location was less than 4.6 mm. ::: Keywords: strawberry harvesting robot, elevated-trough culture, machine vision, nondestructive end-effector, autonomous navigation system, manipulator, sensor ::: DOI: 10.3965/j.ijabe.20120502.001 ::: ::: Citation: Feng Q C, Wang X, Zheng W G, Qiu Q, Jiang K. New strawberry harvesting robot for elevated-trough culture. Int J Agric & Biol Eng, 2012; 5(2): 1
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paper_title: Evaluation of a strawberry-harvesting robot in a field test

paper_content:

We developed a strawberry-harvesting robot, consisting of a cylindrical manipulator, end-effector, machine vision unit, storage unit and travelling unit, for application to an elevated substrate culture. The robot was based on the development concepts of night operation, peduncle handling and task sharing with workers, to overcome the robotic harvesting problems identified by previous studies, such as low work efficiency, low success rate, fruit damage, difficulty of detection in unstable illumination and high cost. In functional tests, the machine vision assessments of fruit maturity agreed with human assessments for the Amaotome and Beni-hoppe cultivars, but the performance for Amaotome was significantly better. Moreover, the machine vision unit correctly detected a peduncle of the target fruit at a rate of 60%. In harvesting tests conducted throughout the harvest season on target fruits with a maturity of 80% or more, the successful harvesting rate of the system was 41.3% when fruits were picked using a suction device before cutting the peduncle, while the rate was 34.9% when fruits were picked without suction. There were no significant differences between the two picking methods in terms of unsuccessful picking rates. The execution time for the successful harvest of a single fruit, including the time taken to transfer the harvested fruit to a tray, was 11.5 s.
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paper_title: Agricultural robot in grape production system

paper_content:

A multipurpose agricultural robot which works in vineyard has been studied. This robot, which consists of a manipulator, a visual sensor, a travelling device and end-effecters, is able to do several works by changing the end-effecters. Four end-effectors for harvesting, berry thinning, spraying and bagging have been developed for this robot system. The harvesting end-effector which grasps and cuts rachis was able to harvest bunches with no damage. The berry thinning end-effector which consists of three unified bunch shape parts. The spraying end-effector sprays the target uniformly, and the bagging end-effector is able to put bags on growing bunches one by one continuously. From the experimental results in a field and laboratory, it was observed that each end-effector could perform efficiently.
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paper_title: An Autonomous Robot for Harvesting Cucumbers in Greenhouses

paper_content:

This paper describes the concept of an autonomous robot for harvesting cucumbers in greenhouses. A description is given of the working environment of the robot and the logistics of harvesting. It is stated that for a 2 ha Dutch nursery, 4 harvesting robots and one docking station are needed during the peak season. Based on these preliminaries, the design specifications of the harvest robot are defined. The main requirement is that a single harvest operation may take at most 10 s. Then, the paper focuses on the individual hardware and software components of the robot. These include, the autonomous vehicle, the manipulator, the end-effector, the two computer vision systems for detection and 3D imaging of the fruit and the environment and, finally, a control scheme that generates collision-free motions for the manipulator during harvesting. The manipulator has seven degrees-of-freedom (DOF). This is sufficient for the harvesting task. The end-effector is designed such that it handles the soft fruit without loss of quality. The thermal cutting device included in the end-effector prevents the spreading of viruses through the greenhouse. The computer vision system is able to detect more than 95% of the cucumbers in a greenhouse. Using geometric models the ripeness of the cucumbers is determined. A motion planner based on the Aa-search algorithm assures collision-free eye-hand co-ordination. In autumn 2001 system integration took place and the harvesting robot was tested in a greenhouse. With a success rate of 80%, field tests confirmed the ability of the robot to pick cucumbers without human interference. On average the robot needed 45 s to pick one cucumber. Future research focuses on hardware and software solutions to improve the picking speed and accuracy of the eye-hand co-ordination of the robot.
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paper_title: Combination of RGB and Multispectral Imagery for Discrimination of Cabernet Sauvignon Grapevine Elements

paper_content:

This paper proposes a sequential masking algorithm based on the K-means method that combines RGB and multispectral imagery for discrimination of Cabernet Sauvignon grapevine elements in unstructured natural environments, without placing any screen behind the canopy and without any previous preparation of the vineyard. In this way, image pixels are classified into five clusters corresponding to leaves, stems, branches, fruit and background. A custom-made sensory rig that integrates a CCD camera and a servo-controlled filter wheel has been specially designed and manufactured for the acquisition of images during the experimental stage. The proposed algorithm is extremely simple, efficient, and provides a satisfactory rate of classification success. All these features turn out the proposed algorithm into an appropriate candidate to be employed in numerous tasks of the precision viticulture, such as yield estimation, water and nutrients needs estimation, spraying and harvesting.
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Title: Deliberation on Design Strategies of Automatic Harvesting Systems: A Survey

Section 1: Introduction
Description 1: Introduce the importance of agriculture and the necessity for mechanization and automation in modern agriculture.

Section 2: Design Strategies
Description 2: Discuss the components and design strategies involved in creating fruit harvesting robots, including recognition, picking, and moving systems.

Section 3: Picking System
Description 3: Detail the requirements and strategies for designing the picking or gripping systems of fruit harvesting robots.

Section 4: Color Camera Recognition System
Description 4: Explain the use of color camera systems for fruit recognition and location in agricultural settings.

Section 5: Multispectral Recognition System
Description 5: Discuss the application and benefits of multispectral recognition systems in detecting and analyzing agricultural products.

Section 6: Fruit Harvesting Robots
Description 6: Provide a historical overview and discuss various developments and advancements in fruit harvesting robots over the years.

Section 7: Discussion
Description 7: Analyze the current state, challenges, and future prospects for commercializing fruit harvesting robots.

Section 8: Conflicts of Interest
Description 8: State any potential conflicts of interest related to the survey.