HATS: マルチアームデータ収集のための人間エージェント遠隔操作システム
HATS: A Human-Agent Teleoperation System for Multi-Arm Data Collection
単一の人間オペレータがMLLMベースのエージェントの支援を受けながら、複数アームの操作データを収集できる遠隔操作システムを提案。2本の主アームを人間が直接操作し、2本の補助アームをエージェントが制御することで、専門家2人によるチームと同等の効率と成功率を達成した。
詳しい要約
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2. 先行研究と比べてどこがすごい？
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著者: Zesen Lin, Jian-Jian Jiang, Haoming Cen, Xiao-Ming Wu, Dandan Zhang, Wei-Shi Zheng
分類: cs.RO
原文アブストラクト
Many real-world manipulation scenarios, such as handling complex collaborative tasks and dealing with large workspaces, require coordination of more than two robotic arms. Consequently, an effective multi-arm teleoperation system is required to collect demonstrations for training coordinated multi-arm manipulation policies. However, existing teleoperation frameworks mainly focus on single-operator or multi-operator setups, facing a practical trade-off between the cognitive load placed on a single operator and the coordination cost incurred by multiple operators. To address this problem, we introduce HATS, a human-agent teleoperation system that enables a single human operator, assisted by an MLLM-based agent, to collect data for multi-arm manipulation tasks. Our system decouples the control space: two primary arms are directly teleoperated by the human, while two assistive arms are controlled by a training-free agent that handles sub-tasks. In addition, the human operator can use voice commands to prevent collisions and correct assistive arm behaviors during execution. Extensive evaluations demonstrate that HATS achieves data collection efficiency and success rates comparable to expert dual-human teams. Moreover, downstream policy evaluations demonstrate the efficacy and quality of the data collected through HATS.
