让用户与机器人共用一个身体,通过自主权动态切换提升辅助操作效率。
One Body, Two Minds: Variable Autonomy Approach for a Co-embodied Robotic Hand

- 用户与机器人共享同一机械手,根据任务阶段自动切换控制权。
- 实验显示任务完成时间缩短23.3%,成功率最高达93.6%。
- 适合需要双手协同的残障人士日常辅助场景。
辅助机器人系统面临根本矛盾:完全自主缺乏用户掌控感,完全手动则需持续认知负担。现有共享自主方法多在独立物理体上运行。本文提出共具身变量自主架构,人类与机器人共享单一物理实体,在任务不同阶段以不同自主水平协作——从物体搜索抓取时的相互自主,到执行阶段的人类主导。我们设计了一款可穿戴式共具身机械手,具备独立‘心智’,通过演示学习的视觉运动扩散策略实现近物自主抓取。抓取完成后系统提示完成,用户可通过无手头部动作操控钻头、喷雾瓶等工具。用户始终拥有撤销权,通过释放手势返回初始状态。与持续协商控制的混合自主不同,本方案实现从全人工到全自主的动态切换,保持物理耦合,形成‘一具双心’范式。44名参与者完成五项双臂任务的用户研究显示,参与者快速适应该模式:任务完成时间平均提升23.3%(p < 0.001,Cohen's d = 0.94),最优策略达成93.6%成功率,整体满意度5.70/7,日常使用意愿5.52/7。本工作验证了共具身变量自主在辅助机器人中的可行性。
原文摘要 · Abstract (English)
Assistive robotic systems face a fundamental trade-off: fully autonomous systems lack user agency, while fully user-controlled systems demand continuous cognitive effort. Existing shared autonomy approaches blend human and robot commands but are mostly deployed in separate physical bodies. We introduce co-embodiment with variable autonomy, where human and robot share a single physical body and operate at different autonomy levels across task phases, from mutual autonomy during object search and grasping to human-dominant control during actuation. We present a co-embodied, wearable robotic hand that has its own ``mind'' and operates with variable autonomy levels. A learning-from-demonstration visuomotor diffusion policy enables autonomous grasping when the user positions the hand near known objects. Once grasped, the system signals completion and the human can actuate the grasped tool (drill, spray bottle, infrared thermometer, lighter, and ice-cream scoop) via hands-free head gestures. The human retains veto authority at all times through a release gesture that returns the system to the initial phase. Unlike blended autonomy, where control is continuously negotiated, our co-embodied approach consists of variable autonomy from full human control to full independent actions while maintaining physical coupling, realizing a one body, two minds paradigm. In a user study with 44 participants performing five bimanual tasks, users rapidly adapted to this ``two minds'' paradigm: completion times improved by 23.3% across trials ($p < 0.001$, Cohen's $d = 0.94$), the best-performing policy variant reached a 93.6% task success rate, and acceptance ratings were high (5.70/7 overall impression, 5.52/7 daily use willingness). This work establishes co-embodiment with variable autonomy as a viable approach for assistive robotics, enabling human-robot collaboration through co-embodiment.
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