高分辨率触觉让机械手像人一样自适应抓取
Embedding high-resolution touch across robotic hands enables adaptive human-like grasping
- 用0.1mm分辨率触觉传感器覆盖70%表面，实现生物仿生感知
- 600次真实场景测试中，抓取成功率显著优于无触觉系统（p<0.0001）
- 适合研究机器人灵巧操作与具身智能的学者和工程师
开发能适应现实动态环境的机械手仍是机器人与机器智能领域的根本挑战。尽管在模拟人类手部运动学与控制算法方面取得显著进展，机器人系统在动态环境中仍难以媲美人类能力，主要由于触觉反馈不足。为此，我们提出F-TAC Hand，一种具有高分辨率触觉感知（0.1mm空间分辨率）的仿生手，其70%表面积覆盖触觉传感器。通过优化手部设计，克服了高分辨率触觉传感器集成的传统难题，同时保持完整运动范围。该手由生成式算法驱动，可合成类人手部姿态，在复杂动态真实场景中展现出稳健抓取能力。600次真实世界测试表明，该具身触觉系统在复杂操作任务中显著优于无触觉引导的替代方案（p<0.0001）。结果为丰富触觉具身在发展高级机器人智能中的关键作用提供了实证支持，为物理感知能力与智能行为间关系提供了新视角。
原文摘要 · Abstract (English)
Developing robotic hands that adapt to real-world dynamics remains a fundamental challenge in robotics and machine intelligence. Despite significant advances in replicating human hand kinematics and control algorithms, robotic systems still struggle to match human capabilities in dynamic environments, primarily due to inadequate tactile feedback. To bridge this gap, we present F-TAC Hand, a biomimetic hand featuring high-resolution tactile sensing (0.1mm spatial resolution) across 70% of its surface area. Through optimized hand design, we overcome traditional challenges in integrating high-resolution tactile sensors while preserving the full range of motion. The hand, powered by our generative algorithm that synthesizes human-like hand configurations, demonstrates robust grasping capabilities in dynamic real-world conditions. Extensive evaluation across 600 real-world trials demonstrates that this tactile-embodied system significantly outperforms non-tactile-informed alternatives in complex manipulation tasks (p<0.0001). These results provide empirical evidence for the critical role of rich tactile embodiment in developing advanced robotic intelligence, offering new perspectives on the relationship between physical sensing capabilities and intelligent behavior.
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