An Auditory and Olfactory Data Fusion Algorithm Based on Spiking Neural Network for Mobile Robot

Abstract

The emergence of bionic sensing technology has brought new inspiration to the control of mobile robot. However, an approach to fusing different modal data to control robot target recognition simply and effectively is a challenging problem at present. In this paper, a mobile robot platform is designed based on auditory and olfactory sensors. The robot obtains the sound information through the microphone array, and the electronic nose senses the chemical gas information, and proposes an auditory and olfactory fusion algorithm based on the spiking neural network, which uniformly encodes the signals of the two modes into spike signals and inputs them to the network for training to realize the target recognition. The designed robot platform can realize the information integration of sound and gas and the recognition of targets, which provides a new method for search and rescue.