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マニピュレーションarXiv:2609.34485

人間とロボットの共有環境における軌道安全なオリエンテーリング

Trajectory-Safe Orienteering for Human-Robot Shared Environments

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時間窓と変動利益を持つオリエンテーリング問題を解くため、離散・連続最適化を分離したDeCoST手法を提案し、人間との衝突を避けつつ高品質なタスク実行を実現した。

著者: Songqun Gao, Elena Basei, Marco Roveri, Luigi Palopoli, Daniele Fontanelli

分類: cs.RO

原文アブストラクト

Orienteering problem (OP) has wide real-world applications and also great potential in human-robot collaboration. However, existing approaches struggle to simultaneously ensure safe and feasible trajectories while achieving high-quality task execution in shared workspaces. To this end, this work studies the OP with time windows and variable profits (OPTWVP). A two-stage DEcoupled discrete-Continuous Optimization with Service-time-guided Trajectory (DeCoST) approach is proposed to effectively solve OPTWVP in shared spaces. Meanwhile, the safety-aware time windows of nodes and the discretized workspace are introduced to ensure collision-free trajectories between the end effector and the human. Preliminary results validate the effectiveness of DeCoST in generating collision-free trajectory plans while preserving the quality of orienteering tasks.

関連論文

PR本紙発行元 EmplifAI