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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

Indonesian

Pembelajaran kebijakan validasi loco-MO operator membutuhkan demonstrasi data yang menangkap gerakan basis terkoordinasi dan gerakan lengan pada implementasi target. Antarmuka bebas robot memungkinkan demonstrasi untuk dikumpulkan secara independen dari robot target, meningkatkan fleksibilitas yang sama, tetapi tanpa secara langsung menangkap perintah-perintah bilateral platform, proprioception, dan pengamatan yang dipasang di tubuh. On-robot teleoperasi pada loco memungkinkan untuk menangkap sinyal ini secara langsung, tetapi membutuhkan antarmuka yang mampu mengendalikan sistem lengkap secara bersamaan. Dokumen ini menyajikan LocoPilot, satu-operator fleksibilitas teleoperasi bilateral dan kerangka pengumpulan data yang diterapkan pada 12-DoFree Unit Go2 quadruped dilengkapi dengan 6-DoFile Piper L Force Manipulator, kamera punggung Intel RealSense D435 dan

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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