Towards Kinematic Actionable Infeasibility Detection in Motion Planning
Overview
A new framework detects motion planning infeasibility by analyzing configuration space topology, validated on 4-DOF and 5-DOF robots. It identifies geometric causes through separating manifolds and uses parallel frontier-expansion for efficiency in high-dimensional spaces. (2026-10-08).
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- arXiv Robotics — research abstractsTowards Kinematic Actionable Infeasibility Detection in Motion Planning
This paper presents a geometry-driven framework for certifying infeasibility in motion planning through an explicit resolution-dependent analysis of configuration space topology. The method traces separating manifolds induced by obstacle boundaries directly in configuration space, enabling both infeasibility detection and identification of geometric causes. A parallel frontier-expansion algorithm is developed for efficient simplicial reconstruction in high-dimensional spaces, validated on 4-DOF and 5-DOF robot scenarios.
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