Adaptive Robot Navigation with Collision Avoidance subject to 2nd-order Uncertain Dynamics

TL;DR

This paper presents an adaptive control approach for collision-free robot navigation in uncertain 2nd-order dynamic systems, extending to multi-robot systems and arbitrary environments with verified simulation results.

Contribution

It introduces a novel adaptive control scheme combining potential-based feedback with uncertainty compensation, applicable to complex environments and multi-robot coordination.

Findings

Guarantees collision-free navigation despite dynamic uncertainties

Extends control scheme to arbitrary star-shaped environments

Validates approach through extensive simulations

Abstract

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.