外观
论文arXiv 2609.079331 个月前
SPOT：面向空间感知的长时程人形机器人遥操作
原文链接：SPOT: Spatial Perception-Oriented Long-Horizon Humanoid Teleoperation（arXiv 2609.07933 · 发布日期：2026-09-07）
SPOT: Spatial Perception-Oriented Long-Horizon Humanoid Teleoperation
SPOT通过宽视场立体显示、自由视角与视觉稳定扩展操作者感知范围，并在多类感知关键人形数据采集任务上验证。
核心要点
- 高质量示范数据成为瓶颈，长时程移动操作要求操作者持续保持空间感知。
- SPOT结合机器人双目鱼眼、宽视场立体显示、视角解耦自由观察和视觉稳定。
- 系统将自我中心立体观测渲染到虚拟半球，使转头不再驱动机器人头部、相机或躯干。
- 在掉落恢复、周边取回、双臂大工作空间操作、精细对准和动态交互中提升效率、精度与恢复速度。
验证范围与局限：验证范围为摘要列举的感知关键人形数据采集任务。
英文摘要 (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.
作者：Lixing Fang, Ziyan Xiong, Sunli Chen, Zhiyang Dou, Chuang Gan
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