In recent years, multiple robots have been successfully applied in various fields, including the handling of logistics factories, agriculture, and disaster relief. This study proposes a novel method for multi-robot deployment and navigation in dynamic environments. To address the problem of location deployment, a grid-based method was used to simplify environmental input information, and a self-clustering method was used to adjust location deployment. To address the problem of navigation, a behavior manager was used as a navigation strategy to control the towards-goal behavior and wall-following behavior (WFB) of mobile robots. An interval type-2 fuzzy controller based on improved particle swarm optimization (IPSO) was proposed to implement the WFB control. The proposed IPSO improved the search ability and enhanced the convergence speed of traditional PSO. Additionally, an escape mechanism was proposed to avoid a dead cycle. Experimental results show that the proposed IPSO is superior to other methods used for WFB and navigation control.
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