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Optimization-Based Path Planning for Industrial Manipulators: Experimental Validation in Additive Manufacturing

2026-11-10 12:25:31
Shiva Ganesh Murali, Valentin Bhend, Deepak Ingole, Gabriele Fadini, Alisa Rupenyan
arXiv_RO
         
Abstract

Robotic additive manufacturing requires joint paths that reconcile robot feasibility with process-specific geometry. We develop an offline optimization-based path planner that combines joint-path regularity and self-collision penalties with process costs and constraints, so that a new process enters through its own reference, residuals, and tolerances. Full-path and boundary-coupled chunked optimization handle references of different lengths. Iterative Weight Tuning (IWT) determines the cost weights from the gaps between Key Performance Indicators (KPIs) and their targets. In carbon-fiber winding and robotic 3D printing, the planned paths meet the geometric tolerances and all KPI targets, and both paths are executed on a UR10e, without extrusion for printing, with joint-level tracking recorded during execution.

Abstract (translated)

URL

https://arxiv.org/abs/2611.13983

PDF

https://arxiv.org/pdf/2611.13983.pdf

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