Complete Motion Planning using Workspace-Fibered Decomposition for nR-Planar Manipulator
Aayush Rath, Antony Thomas
Abstract
We propose a workspace-fibered decomposition framework for motion planning in nR planar redundant manipulators operating in cluttered environments. Rather than planning directly in the full n-dimensional configuration space, the method incrementally constructs obstacle-constrained reachable workspaces of lower-dimensional non-redundant sub-chains and recursively lifts them through redundant orientation fibers. This yields a sequence of reduced planning manifolds that preserve branch-consistent reachability structure while avoiding explicit construction of the full configuration-space obstacle geometry. We first establish that, for planar position-only manipulators, the obstacle-constrained reachable workspace induced by the minimal non-redundant sub-chain provides an exact characterization of feasibility with respect to the connected component of the start configuration, enabling early infeasibility detection prior to introducing redundant degrees of freedom (DOF). We then introduce an incremental fiber-lifting procedure that propagates reachable workspace structure through successive redundant links while enforcing local inverse-kinematic branch consistency using Jacobian determinant continuity constraints. The resulting representation admits efficient reduced-space planning directly on recursively-constructed workspace-fiber manifolds. Experimental results on redundant nR planar manipulators demonstrate that the proposed construction preserves collision-free connectivity structure across successive lifting stages while substantially reducing collision checking complexity relative to direct configuration space reasoning.
Create a lesson
Related papers
rMuscle: Robotic Muscle Memory for Efficient Vision-Language-Action Model Inference
Kaijun Zhou, Zhiyang Li, Le Chen et al.
ElastiQP: An Always-Feasible QP Solver for Constrained Robot Control
Daniel Morton, Jon Arrizabalaga, Zachary Manchester et al.
"What's going to happen after I'm gone?": Parent Perspectives on Technology in Supporting Independent Living for Adults with Intellectual Disabilities
Alexander Tyshka, Andrea Macklem-Zabel, Absalat Getachew et al.
Learning Holistic Whole-Body Loco-Manipulation with a Bipedal Mobile Manipulator
Zhongyu Chen, Yuxuan Nai, Qian Chen et al.
CaSCo: Cascade-Aware Soft-Collision Motion Planning
Shivaram Kumar, Gaoyuan Liu, Yoonchang Sung
Examining the Difference in Human Behavior Between Virtual and Real-World Human-Robot Teaming
Sean Dallas, Absalat Getachew, Motaz AbuHijleh et al.