Using a Self-Clustering Algorithm and Type-2 Fuzzy Controller for Multi-robot Deployment and Navigation in Dynamic Environments

Abstract

This study proposes a novel method for multi-robot deployment and navigation under dynamic environments. To automatically determine the location deployment of multiple robots, a grid-based method and self-clustering algorithm (SCA) were used to simplify the environmental information and automatically deploy robot locations. In the navigation process, a behavior selector automatically turns on towards goal mode or wall-following mode (WFM) depending on environmental conditions. WFM control adopts an interval type-2 fuzzy controller (IT2FC). The parameters of the IT2FC are adjusted by using the dynamic group whale optimization algorithm (DGWOA). The proposed DGWOA uses a dynamic group and Levy flight strategy to overcome the problem of falling into a local minimum solution. Experimental results reveal that the proposed method can successfully complete navigation tasks under dynamic environments.