给机器人装上可动脖子，让远程操作更自然高效。
Learning to Look Around: Enhancing Teleoperation and Learning with a Human-like Actuated Neck
- 用5自由度可动脖子模拟人类头部动作，提升环境感知。
- 在7个任务中显著提升操作效率，降低认知负担。
- 帮助训练自主策略，改善空间感知与适应性。
我们提出一种集成5自由度可动颈部的遥操作系统，旨在复现自然的人类头部运动与感知方式。通过实现窥视、倾斜等行为，该系统为操作员提供更直观、全面的环境视野，从而提升任务表现，减轻认知负荷，并支持复杂的全身操控。我们在七个具有挑战性的遥操作任务中验证了自然感知的优势，表明可动颈部显著扩展了远程操作的视野范围与执行效率。此外，我们研究其在模仿学习中训练自主策略的作用：在三个任务中，相比静态广角相机，可动颈部提升了空间感知能力，减少了分布偏移，并支持针对特定任务的自适应调整。
原文摘要 · Abstract (English)
We introduce a teleoperation system that integrates a 5 DOF actuated neck, designed to replicate natural human head movements and perception. By enabling behaviors like peeking or tilting, the system provides operators with a more intuitive and comprehensive view of the environment, improving task performance, reducing cognitive load, and facilitating complex whole-body manipulation. We demonstrate the benefits of natural perception across seven challenging teleoperation tasks, showing how the actuated neck enhances the scope and efficiency of remote operation. Furthermore, we investigate its role in training autonomous policies through imitation learning. In three distinct tasks, the actuated neck supports better spatial awareness, reduces distribution shift, and enables adaptive task-specific adjustments compared to a static wide-angle camera.
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