計画レベルの意図予測を備えた移動ロボットの共有制御フレームワーク
A Shared Control Framework for Mobile Robots with Planning-Level Intention Prediction
人間の将来の動きを「意図領域」として予測し、経路再計画と組み合わせて移動ロボットを支援する共有制御手法を提案。シミュレーションのみで学習し、実機実験で作業負担の軽減と安全性向上を確認した。
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？
※ AIが要旨から生成した要約です。正確性は原文をご確認ください。
著者: Jinyu Zhang, Lijun Han, Feng Jian, Lingxi Zhang, Hesheng Wang
分類: cs.RO
原文アブストラクト
In mobile robot shared control, effectively understanding human motion intention is critical for seamless human-robot collaboration. This paper presents a novel shared control framework featuring planning-level intention prediction. A path replanning algorithm is designed to adjust the robot's desired trajectory according to inferred human intentions. To represent future motion intentions, we introduce the concept of an intention domain, which serves as a constraint for path replanning. The intention-domain prediction and path replanning problems are jointly formulated as a Markov Decision Process and solved through deep reinforcement learning. In addition, a Voronoi-based human trajectory generation algorithm is developed, allowing the model to be trained entirely in simulation without human participation or demonstration data. Extensive simulations and real-world user studies demonstrate that the proposed method significantly reduces operator workload and enhances safety, without compromising task efficiency compared with existing assistive teleoperation approaches.
