Data-driven electrical resistance tomography for robotic large-area tactile sensing

Abstract

In this article, a novel DDERT sensing method is proposed for large-area tactile sensing. In particular, the method utilizes a generative model to reconstruct the boundary measurement voltage of the ERT sensor into a tactile image. To improve the quality of tactile imaging, a spatial attention mechanism is incorporated into the model. Additionally, a mask constraint is introduced as prior information to ensure that the generated images contain more accurate tactile information in areas of contact with objects. Experimental results validate the proposed method is effective for the large-area robotic tactile sensing. Furthermore, the prototype of the ERT-based tactile sensor is fabricated and the sensing performance is evaluated in real robotic applications.