Globally Guided Reactive Motion Planning for Non-Prehensile Transport in Cluttered Space

Non-prehensile transportation holds significant promise for robotic service applications. However, existing methods often struggle to balance global navigability in complex scenarios with local reactivity. To address this challenge, this letter presents a reactive motion planning framework for robotic non-prehensile transportation in cluttered environments. To adapt to environmental changes, the framework employs a proactive periodic replanning strategy coupled with a passive, time-to-collision-triggered safety mechanism. Both components rely on a hierarchical trajectory generator that utilizes a constrained path planner to provide global geometric guidance for circumventing local minima, followed by a two-stage optimization. To enhance computational efficiency, the optimization leverages soft penalties instead of hard constraints to refine trajectories and promote contact stability. Comparative results validate the proposed method's advantages, while extensive experiments characterize the performance boundaries of this soft-constraint formulation.