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This research addresses the data bottleneck in training general-purpose humanoid robots by introducing SPOT, a VR teleoperation system that extends an operator's spatial perception horizon. By decoupling visual exploration from robot actuation through a wide-field stereoscopic display and viewpoint-decoupled controls, SPOT enables stable, long-horizon loco-manipulation tasks without interfering with the robot's motion. The system demonstrates improved efficiency and accuracy in complex scenarios like drop recovery and large-workspace manipulation, offering a scalable solution for collecting high-quality demonstration data.
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SPOT: Spatial Perception-Oriented Long-Horizon Humanoid Teleoperation

arXiv3 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2609.07933v1 Announce Type: new Abstract: High-quality demonstration data is becoming a central bottleneck for training general-purpose humanoid robots. While recent humanoid teleoperation systems have made substantial progress in retargeting human motion to robot motion, long-horizon loco-manipulation requires another capability: operators must maintain task-relevant spatial awareness over time, e.g., object locations, surrounding environments, the robot's pose. We call the extent of this awareness the operator's perceptual horizon. However, existing methods often shorten this: narrow views miss peripheral events, robot-mounted cameras become unstable during locomotion, and coupled head-view control makes looking around interfere with robot motion. We present SPOT, a Spatial Perception-Oriented VR Teleoperation system for collecting long-horizon humanoid demonstration data by providing extended perceptual horizon. SPOT combines a robot-mounted binocular fisheye camera, a wide-field stereoscopic display, viewpoint-decoupled free-looking, and visual stabilization to provide a robot-centric view that is wide, stable, and actively inspectable. Unlike conventional egocentric interfaces, SPOT decouples visual exploration from robot actuation: the egocentric stereo observation is rendered on a virtual hemisphere around the operator, so natural head rotations change where the operator looks within the wide-field view rather than commanding the robot head, camera, or torso. We evaluate SPOT on perception-critical humanoid data-collection tasks spanning drop recovery, peripheral retrieval, large-workspace bimanual manipulation, fine alignment, and dynamic interaction. SPOT improves efficiency, accuracy, and recovery speed, demonstrating its effectiveness for user-friendly and scalable long-horizon humanoid data collection.

Abstract:High-quality demonstration data is becoming a central bottleneck for training general-purpose humanoid robots. While recent humanoid teleoperation systems have made substantial progress in retargeting human motion to robot motion, long-horizon loco-manipulation requires another capability: operators must maintain task-relevant spatial awareness over time, e.g., object locations, surrounding environments, the robot's pose. We call the extent of this awareness the operator's perceptual horizon. However, existing methods often shorten this: narrow views miss peripheral events, robot-mounted cameras become unstable during locomotion, and coupled head-view control makes looking around interfere with robot motion. We present SPOT, a Spatial Perception-Oriented VR Teleoperation system for collecting long-horizon humanoid demonstration data by providing extended perceptual horizon. SPOT combines a robot-mounted binocular fisheye camera, a wide-field stereoscopic display, viewpoint-decoupled free-looking, and visual stabilization to provide a robot-centric view that is wide, stable, and actively inspectable. Unlike conventional egocentric interfaces, SPOT decouples visual exploration from robot actuation: the egocentric stereo observation is rendered on a virtual hemisphere around the operator, so natural head rotations change where the operator looks within the wide-field view rather than commanding the robot head, camera, or torso. We evaluate SPOT on perception-critical humanoid data-collection tasks spanning drop recovery, peripheral retrieval, large-workspace bimanual manipulation, fine alignment, and dynamic interaction. SPOT improves efficiency, accuracy, and recovery speed, demonstrating its effectiveness for user-friendly and scalable long-horizon humanoid data collection.

Robotics (cs.RO)

arXiv:2609.07933 [cs.RO]

(or arXiv:2609.07933v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2609.07933 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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