Robotic surface exploration with vision and tactile sensing for cracks
  detection and characterisation
Francesca Palermo Bukeikhan Omarali Changae Oh Kaspar Althoefer Ildar Farkhatdinov
This paper presents a novel algorithm for crack localisation and detection
based on visual and tactile analysis via fibre-optics. A finger-shaped sensor
based on fibre-optics is employed for the data acquisition to collect data for
the analysis and the experiments. To detect the possible locations of cracks a
camera is used to scan an environment while running an object detection
algorithm. Once the crack is detected, a fully-connected graph is created from
a skeletonised version of the crack. A minimum spanning tree is then employed
for calculating the shortest path to explore the crack which is then used to
develop the motion planner for the robotic manipulator. The motion planner
divides the crack into multiple nodes which are then explored individually.
Then, the manipulator starts the exploration and performs the tactile data
classification to confirm if there is indeed a crack in that location or just a
false positive from the vision algorithm. If a crack is detected, also the
length, width, orientation and number of branches are calculated. This is
repeated until all the nodes of the crack are explored.
  In order to validate the complete algorithm, various experiments are
performed: comparison of exploration of cracks through full scan and motion
planning algorithm, implementation of frequency-based features for crack
classification and geometry analysis using a combination of vision and tactile
data. From the results of the experiments, it is shown that the proposed
algorithm is able to detect cracks and improve the results obtained from vision
to correctly classify cracks and their geometry with minimal cost thanks to the
motion planning algorithm.