A Multirobot Cooperative Area Coverage Search Algorithm Based on Bioinspired Neural Network in Unknown Environments

Abstract

This article proposes a novel approach based on a bioinspired neural network (BIN) for multirobot area coverage search in unknown environments. We obtain the dynamic environment information in the search process of the multirobot by combining the BIN model with the grid map. We, then, design a search objective function to guide robots to explore the task area by applying the distributed model prediction control policy. Moreover, we further improve the search efficiency through a collaborative decision-making mechanism among robots. Finally, we conduct simulation studies, which demonstrate the effectiveness and superiority of the proposed approach.