Monitoring Soft Shape Surface Deformation via Optical Images for the Distinction of Contact State

Abstract

The deformability of elastomer surfaces offers the opportunity to capture multimodal physical information, which opens up possibilities for applications in intelligent interactive systems and flexible electronics. Accurately identifying the surface deformation of elastomers has been a key issue for understanding the contact state in a soft touch. However, effective monitoring of the deformed surface topography during soft‐touch processes is difficult due to the complexity of interfacial deformation. Herein, the optical detection method based on an ideal diffuse reflection model is proposed to monitor the deformation of the elastomer, enabling the acquisition of a spatially continuous deformation of the surface in a soft touch. This optical system with the parallel incident light can distinguish the elastomers’ surface deformation field by constructing the correlation between the reflected light irradiance and the surface deformation angle. This method allows for the perception of the contact area. Through the deep learning method, the recognition rate can reach more than 84.24% when there are slight differences in the contact of objects with different geometric shapes. The design offers valuable insights for contact state detection tasks and facilitates soft‐touch sensing functions through the high precision of optical signal acquisition.

Improving the Representation and Extraction of Contact Information in Vision-based Tactile Sensors Using Continuous Marker Pattern

“…actile sensing [1]- [5] is significant in various domains, including robotics [6] [7], electronic skin [8] [9], and human-computer interaction [10] [11]. Nowadays, the detection scenarios tend to be more complex and the detection requirements are improving increasingly.…”