Optimization-Based Path Planning for Industrial Manipulators: Experimental Validation in Additive Manufacturing
Overview
This paper introduces an offline optimization-based path planner designed for robotic additive manufacturing, combining joint-path regularity and self-collision penalties with process costs and constraints. The approach handles references of different lengths using full-path and boundary-coupled chunked optimization and employs Iterative Weight Tuning (IWT) to determine cost weights from gaps between Key Performance Indicators (KPIs) and targets. Experimental validation on a UR10e robot demonstrates that planned paths for carbon-fiber winding and robotic 3D printing meet geometric tolerances and KPI targets, with joint-level tracking recorded during execution.
Generated from attributed reports · Updated 3 hours ago
Event evidence and corrections
0 attributed source owners. Ownership does not establish independent confirmation. Quantities are reported separately and are never added together.
No current evidence-backed claims. Missing information remains not reported.
Report timeline
Follow attributed reports and material updates.
- arXiv Robotics — research abstractsSignalOptimization-Based Path Planning for Industrial Manipulators: Experimental Validation in Additive Manufacturing
This paper introduces an offline optimization-based path planner designed for robotic additive manufacturing, combining joint-path regularity and self-collision penalties with process costs and constraints. The approach handles references of different lengths using full-path and boundary-coupled chunked optimization and employs Iterative Weight Tuning (IWT) to determine cost weights from gaps between Key Performance Indicators (KPIs) and targets. Experimental validation on a UR10e robot demonstrates that planned paths for carbon-fiber winding and robotic 3D printing meet geometric tolerances and KPI targets, with joint-level tracking recorded during execution.
Event coverage history
There is not enough continuous observation data to show a trend.
Timezone · UTC
Article dates follow your selected timezone. Briefing editions use Hong Kong time (UTC+8).