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LocoPilot: Single-Operator Bilateral Teleoperation for Loco-Manipulation Policy Learning

Antonio Langella, Giovanni Minelli, Giovanni Dessy, Lorenzo Amatucci, Giulio Turrisi, Victor Barasuol, Claudio Semini · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.27998 · cited by 0 works (OpenAlex) · open-access PDF

Russian

Обучение правилам локомотивации кода требует демонстраций данных, которые захватывают скоординированное движение базы и руки на целевом варианте осуществления. Робот-бесплатные интерфейсы позволяют собирать демонстрации независимо от целевого робота, увеличивая одинаковую гибкость обратной связи, но без прямого захвата платформенных команд, proprioception и телемонтированных наблюдений. На робот-телеоперация на локомотиве позволяет захватывать эти сигналы напрямую, но требует интерфейса, способного одновременно управлять полной системой. Эта статья представляет LocoPilot, однооператорную двустороннюю телеоперацию и рамку сбора данных, реализованную на 12-DoFree Unit Go2 quadruped, оснащенный 6-DoFile Piper L

Machine translation (Meta M2M100); the English original follows.

Abstract

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

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Topics: Teleoperation, Haptic technology, Computer science, Interface (matter), Pipeline (software), Retargeting

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