DTactive: A Vision-Based Tactile Sensor with Active Surface

Jikai Xu*,1,2,  Lei Wu*,1,2,  Changyi Lin3,  Ding Zhao3,  Huazhe Xu1,4,5
1Shanghai Qi Zhi Institute,  2Huazhong University of Science and Technology, 
3Carnegie Mellon University,  4Tsinghua University,  5Shanghai Artificial Intelligence Laboratory
QZ HUST CMU THU SAIL

Abstract

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.

Design and Fabrication

Design and Fabrication

Rolling Manipulation Control Framework

Design and Fabrication

Demo