Minimal Path Violation Problem with Application to Fault Tolerant Motion Planning of Manipulators

Abstract

Failure of any component in a robotic system during operation is a critical concern, and it is essential to address such incidents promptly. This work investigates a novel technique to recover from failures or changes in the configuration space while avoiding expensive re-computation or re-planning. We propose the Minimal Path Violation (MPV) concept to find the best feasible path with minimal re-configurations. The algorithm ranks pathways based on visibility, expansiveness, and cost. We perform experiments with articulated 3 DOF to 28 DOF robots ranging from serial linkage robots, Kuka YouBots, and PR2 robots. Our results show that our method outperforms existing optimal planners in computation time, total nodes, and path cost while preserving path feasibility in changed configuration space.