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

1 reports1 reporting sourcesUpdated 10 days ago

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This paper presents LocoPilot, a single-operator bilateral teleoperation framework for loco-manipulation policy learning. It enables direct capture of robot-specific signals like proprioception and body-mounted observations without motion-capture instrumentation. The system integrates a 12-DoF quadruped with a 6-DoF manipulator, using two handheld controllers and a follower arm for force feedback. A ROS~2 pipeline records synchronized multimodal data and a unified 11D action space, validated through deployment on a physical robot without retargeting or additional inverse kinematics.

From arXiv Robotics — research abstracts

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Reported quantity · degrees of freedom: 12 other · Basis not reported
Supporting report

“tion 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-Do”

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Supporting report

“tions 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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Evidence dependency changes (2)
  • 2026-10-30T21:59:17.059Z · evidence updated · source revision 1. Evidence extraction was updated; current source attributions are shown above.
  • 2026-10-30T21:58:57.488Z · evidence updated · source revision 1. Evidence extraction was updated; current source attributions are shown above.

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10/21
  1. arXiv Robotics — research abstractsSignal
    LocoPilot: Single-Operator Bilateral Teleoperation for Loco-Manipulation Policy Learning

    This paper presents LocoPilot, a single-operator bilateral teleoperation framework for loco-manipulation policy learning. It enables direct capture of robot-specific signals like proprioception and body-mounted observations without motion-capture instrumentation. The system integrates a 12-DoF quadruped with a 6-DoF manipulator, using two handheld controllers and a follower arm for force feedback. A ROS~2 pipeline records synchronized multimodal data and a unified 11D action space, validated through deployment on a physical robot without retargeting or additional inverse kinematics.

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