Ultra-stable and tough bioinspired crack-based tactile sensor for small legged robots

Abstract For legged robots, collecting tactile information is essential for stable posture and efficient gait. However, mounting sensors on small robots weighing less than 1 kg remain challenges in terms of the sensor’s durability, flexibility, sensitivity, and size. Crack-based sensors featuring ultra-sensitivity, small-size, and flexibility could be a promising candidate, but performance degradation due to crack growing by repeated use is a stumbling block. This paper presents an ultra-stable and tough bio-inspired crack-based sensor by controlling the crack depth using silver nanowire (Ag NW) mesh as a crack stop layer. The Ag NW mesh inspired by skin collagen structure effectively mitigated crack propagation. The sensor was very thin, lightweight, sensitive, and ultra-durable that maintains its sensitivity during 200,000 cycles of 0.5% strain. We demonstrate sensor’s feasibility by implementing the tactile sensation to bio-inspired robots, and propose statistical and deep learning-based analysis methods which successfully distinguished terrain type.