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.

Robotics (cs.RO); Systems and Control (eess.SY)

arXiv:2503.17589 [cs.RO]

(or arXiv:2503.17589v3 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2503.17589 Focus to learn more arXiv-issued DOI via DataCite

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