From Kinematic Motion Planners to Dynamic Autonomous Navigation with Obstacle Avoidance (Extended version)

Abstract

Kinematic motion planners are among the most widely used control approaches in robotic applications. By modeling the robot as a first-order system, they generate a feedback-based desired velocity field that guides the robot toward a target while avoiding obstacles. However, extending such feedback planners to systems with higher-order dynamics, while preserving safety and stability properties, is not a straightforward task. In the present work, we propose an approach that adapts existing feedback-based kinematic motion planners to second-order autonomous systems while retaining their safety and almost global asymptotic stability guarantees. We consider two general classes of kinematic motion planners: those derived from navigation functions and those defined directly through desired velocity fields without relying on an underlying navigation function. To validate the proposed methodology, two feedback-based kinematic motion planners are adapted to second-order systems and evaluated both in simulations and experimentally.

arXiv comment20 pages, 14 figures