Adaptive robot navigation with collision avoidance subject to 2nd-order uncertain dynamics

This paper considers the problem of robot motion planning in a workspace with obstacles for systems with uncertain 2nd-order dynamics. In particular, we combine closed form potential-based feedback controllers with adaptive control techniques to guarantee the collision-free robot navigation to a predefined goal while compensating for the dynamic model uncertainties. We base our findings on sphere world-based configuration spaces, but extend our results to arbitrary star-shaped environments by using previous results on configuration space transformations. Moreover, we propose an algorithm for extending the control scheme to decentralized multi-robot systems. Finally, extensive simulation results verify the theoretical findings. (c) 2020 Elsevier Ltd. All rights reserved.

Automated summary

This paper addresses the problem of robot motion planning in workspaces with obstacle and uncertain 2nd-order dynamics, combining potential-based feedback controllers with adaptive control techniques. The study is based on sphere world-based configuration spaces and extends the results to arbitrary star-shaped environments, proposing an algorithm for decentralized multi-robot systems. Theoretical findings are verified through extensive simulation results.