让触觉传感器能主动移动表面，实现精准抓握翻转
DTactive: A Vision-Based Tactile Sensor with Active Surface
- 通过可动表面结合视觉感知，实现触觉与操作同步
- 在9个训练物上误差低于12°，3个新物体也低于19°
- 适合需要高精度手内操作的机器人任务
视觉触觉传感器的发展显著提升了机器人在接触密集型任务中的感知与操作能力。本文提出DTactive，一种具备主动表面的新型视觉触觉传感器。它在继承并改进DTact三维形变重建方法的基础上，集成机械传动机构，使表面具备运动能力。该设计使传感器可同时完成触觉感知与手内操作中的表面移动。结合传感器获取的高分辨率触觉图像及传动机构的磁编码器数据，我们提出一种基于学习的方法，实现手内操作中角度轨迹的精确控制。实验表明，在多种物体上成功实现[-180°,180°]范围内的精确滚动操作，9个训练物体的均方根误差小于12°，3个新物体小于19°。结果证明DTactive在有效性、鲁棒性与精度方面具备手内操作潜力。
原文摘要 · Abstract (English)
The development of vision-based tactile sensors has significantly enhanced robots' perception and manipulation capabilities, especially for tasks requiring contact-rich interactions with objects. In this work, we present DTactive, a novel vision-based tactile sensor with active surfaces. DTactive inherits and modifies the tactile 3D shape reconstruction method of DTact while integrating a mechanical transmission mechanism that facilitates the mobility of its surface. Thanks to this design, the sensor is capable of simultaneously performing tactile perception and in-hand manipulation with surface movement. Leveraging the high-resolution tactile images from the sensor and the magnetic encoder data from the transmission mechanism, we propose a learning-based method to enable precise angular trajectory control during in-hand manipulation. In our experiments, we successfully achieved accurate rolling manipulation within the range of [ -180°,180° ] on various objects, with the root mean square error between the desired and actual angular trajectories being less than 12° on nine trained objects and less than 19° on three novel objects. The results demonstrate the potential of DTactive for in-hand object manipulation in terms of effectiveness, robustness and precision.
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