Self-powered artificial vibrissal system with anemotaxis behavior

Abstract

Anemotaxis behaviors inspired by rats have tremendous potential in efficiently processing perilous search and rescue operations in the physical world, but there is still lack of hardware components that can efficiently sense, encode, and recognize wind signal. Here, we report an artificial vibrissal system consisting of a self-powered carbon black sensor and threshold-switching HfO 2 memristor. By integrating a forming HfO 2 memristor with a self-powered angle-detecting hydro-voltaic sensor, the spiking sensory neuron can synchronously perceive and encode wind, humidity, and temperature signals into spikes with different frequencies. Furthermore, to validate the self-powered artificial vibrissal system with anemotaxis behavior, a robotic car with equipped artificial vibrissal system tracks trajectory toward the air source has been demonstrated. This design not only addresses the high energy consumption and low computing issues of traditional sensory system but also introduces the multimode functionalities, therefore promoting the construction of neuromorphic perception systems for neurorobotics.