Autonomous Navigation of Micro Air Vehicles in Warehouses Using
  Vision-based Line Following
Ling Shuang Soh Hann Woei Ho
In this paper, we propose a vision-based solution for indoor Micro Air
Vehicle (MAV) navigation, with a primary focus on its application within
autonomous warehouses. Our work centers on the utilization of a single camera
as the primary sensor for tasks such as detection, localization, and path
planning. To achieve these objectives, we implement the HSV color detection and
the Hough Line Transform for effective line detection within warehouse
environments. The integration of a Kalman filter into our system enables the
camera to track yellow lines reliably. We evaluated the performance of our
vision-based line following algorithm through various MAV flight tests
conducted in the Gazebo 11 platform, utilizing ROS Noetic. The results of these
simulations demonstrate the system capability to successfully navigate narrow
indoor spaces. Our proposed system has the potential to significantly reduce
labor costs and enhance overall productivity in warehouse operations. This work
contributes to the growing field of MAV applications in autonomous warehouses,
addressing the need for efficient logistics and supply chain solutions.