Informed Circular Fields for Global Reactive Obstacle Avoidance of Robotic Manipulators

Abstract: In this paper a global reactive motion planning framework for robotic manipulators in complex dynamic environments is presented. In particular, the circular field predictions (CFP) planner from Becker et al. (2021) is extended to ensure obstacle avoidance of the whole structure of a robotic manipulator. Towards this end, a motion planning framework is developed that leverages global information about promising avoidance directions from arbitrary configuration space motion planners, resulting in improved global trajectories while reactively avoiding dynamic obstacles and decreasing the required computational power. The resulting motion planning framework is tested in multiple simulations with complex and dynamic obstacles and demonstrates great potential compared to existing motion planning approaches. Keywords: Autonomous robotic systems, Robots manipulators, Guidance navigation and control, Motion Planning, Real-Time Collision Avoidance 1. INTRODUCTION RRT planner has been improved and extended to different variants, e.g., the RRT-connect improves the runtime Motivation: Classical industrial robotic applications require (Kuffner and LaValle, 2000), whereas the asymptotically fences or other peripheral safety installations to optimal RRT* decreases the resulting path length (Karaman ensure seamless production processes and the safety of and Frazzoli, 2011).