Path Planning and Collision Prevention based on Computer Vision applied to a Mini-sized Multi-robot Testbed

Abstract

A practical testbed is crucial to reduce the gap between theory and real-world applications. Path-planning and collision prevention routines are essential for a reliable operation of these multi-robot platforms, so increasingly complex control algorithms can be proposed, designed and tested. This paper describes the recent progress made on the functionality of a mini-sized multi-robot testbed that runs based on ROS (Robotic Operating System). A high-level path planner, a collision prevention routine and motion controllers are proposed as part of the expansion to more complex applications that can run on the testbed. A PID-based orientation controller and an Inverse Kinematics position controller are designed and compared as viable solutions for following the waypoints generated by the high-level path planner. Improvements on software modularity, scalability and the addition of an extra mobile agent also comprise the main improvements for this new iteration of the testbed. The results of the path-planning routine, as well as the performance of the motion controllers are presented and discussed.