LocoPilot：四足ロボットの脚と腕を同時に操る単独遠隔操作によるロコマニピュレーション学習
LocoPilot: Single-Operator Bilateral Teleoperation for Loco-Manipulation Policy Learning
四足ロボットに搭載したアームを、別のリーダーアームとコントローラで単独操作し、力覚フィードバック付きで脚と腕の協調動作データを収集する遠隔操作フレームワークを提案した。
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: Antonio Langella, Giovanni Minelli, Giovanni B. Dessy, Lorenzo Amatucci, Giulio Turrisi, Victor Barasuol, Claudio Semini
分類: cs.RO
原文アブストラクト
Learning loco-manipulation policies requires demonstrations that capture coordinated base and arm motion on the target embodiment. Robot-free interfaces allow demonstrations to be collected independently of the target robot, increasing flexibility but without directly capturing platform-specific commands, proprioception, and body-mounted observations. On-robot teleoperation allows to capture these signals directly, but requires an interface capable of commanding the complete system concurrently. This paper presents LocoPilot, a single-operator bilateral teleoperation and data-collection framework implemented on a 12-DoF Unitree Go2 quadruped equipped with a 6-DoF AgileX Piper L manipulator, an Intel RealSense D435 wrist camera, and an Intel RealSense D405 head camera. A second 6-DoF Piper L arm, used as the leader and two handheld controllers provide simultaneous control of the base, body posture, manipulator, and gripper. The follower arm interaction forces are estimated without a dedicated force/torque sensor and rendered to the operator through a passivity-constrained haptic channel. A ROS~2 pipeline records synchronized multimodal observations together with a unified 11D action shared by teleoperation and policy deployment. Compared to prior work, LocoPilot uniquely unifies robot-in-the-loop legged data collection, force feedback without motion-capture instrumentation, and the same action interface at deployment. We evaluate the interface across multiple loco-manipulation tasks and validate the complete collection-to-deployment pipeline by fine-tuning MolmoAct2 \cite{MOLMO} on pick-and-place demonstrations and deploying on the physical robot without action retargeting or additional inverse kinematics. Code available at: https://github.com/iit-DLSLab/LocoPilot