Investigation of Multi-Physical Sensing in Soft Robots via Signal Transduction Mechanisms

The recent days of Soft robots exhibit unique advantages in complex interaction scenarios due to their compliance and inherent safety. However, the unique advantages substantially increase the difficulty of designing reliable perception systems. In practical applications, a single sensing mechanism often fails to ensure stable and robust perception. Therefore, this work presents a systematic analysis of multi-physics perception approaches in soft robotics from the perspective of signal transduction mechanisms. This article will concentrate on the topic of the features and uses of three common sensing systems, which are electrical, optical, and sound, in terms of real-time response and deep information acquisition. Looked at are the roles of multimodal integration and intelligent decoding in reducing signal uncertainty and making perception more reliable. It is shown that multi-physics perception can effectively compensate for the limitations of single-modality sensing, providing system-level theoretical insights for the design and application of soft robotic perception systems.