用视觉捕捉足部变形，让机器人像皮肤一样感知地面。
Soft Surfaced Vision-Based Tactile Sensing for Bipedal Robot Applications
- 用柔软表面+视觉传感，光学记录足地接触形变。
- 能实时计算压力中心、识别地形、检测接触特征。
- 适合需要稳定行走的双足机器人，提升环境感知能力。
腿式行走依赖具身感知，即身体与环境互动中产生的感知。本文提出一种软表面、基于视觉的足部触觉传感器，为双足机器人赋予类皮肤的可变形层，通过光学方式捕捉接触变形，将足地交互转化为丰富的触觉信号。从接触图像流中，该方法可估计接触位姿（位置与方向）、可视化剪切力、计算压力中心（CoP）、分类地形并检测接触区域的几何特征。我们在倾斜平台和视觉遮蔽条件下验证了这些能力，结果表明足端触觉反馈能显著提升平衡控制与地形感知能力，超越仅依赖本体感知的效果。研究显示，将触觉感知集成至腿式机器人的足部，可增强稳定性、适应性与环境意识，为更柔顺、智能的运动系统提供新方向。补充视频请访问：https://youtu.be/ceJiy9q_2Aw
原文摘要 · Abstract (English)
Legged locomotion benefits from embodied sensing, where perception emerges from the physical interaction between body and environment. We present a soft-surfaced, vision-based tactile foot sensor that endows a bipedal robot with a skin-like deformable layer that captures contact deformations optically, turning foot-ground interactions into rich haptic signals. From a contact image stream, our method estimates contact pose (position and orientation), visualizes shear, computes center of pressure (CoP), classifies terrain, and detects geometric features of the contact patch. We validate these capabilities on a tilting platform and in visually obscured conditions, showing that foot-borne tactile feedback improves balance control and terrain awareness beyond proprioception alone. These findings suggest that integrating tactile perception into legged robot feet improves stability, adaptability, and environmental awareness, offering a promising direction toward more compliant and intelligent locomotion systems. For the supplementary video, please visit: https://youtu.be/ceJiy9q_2Aw
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