産業用マニピュレータの最適化ベース経路計画：積層造形における実験的検証
Optimization-Based Path Planning for Industrial Manipulators: Experimental Validation in Additive Manufacturing
ロボット積層造形向けに、関節経路の規則性や自己衝突ペナルティとプロセスコスト・制約を統合したオフライン最適化経路計画を開発し、炭素繊維巻きと3DプリンティングでUR10e上での実行検証を行った。
詳しい要約
1. どんなもの？
2. 先行研究と比べてどこがすごい？
3. 技術・手法の肝は？
4. どうやって有効だと検証した？
5. 議論はある？
6. 次に読むべき論文は？
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著者: Shiva Ganesh Murali, Valentin Bhend, Deepak Ingole, Gabriele Fadini, Alisa Rupenyan
分類: cs.RO, math.OC
原文アブストラクト
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.