AN IMPROVED IMMUNE-INSPIRED SELF-HEALING APPROACH BASED ON SWARM AGGREGATION ALGORITHM FOR MULTI-ROBOT SYSTEM

Jianjun Ni, Min Tang, Yangju Liu, Oghenemuero Gordon, and Chengming Luo

Keywords

Self-healing system, Swarm aggregation algorithm, Multi-robot system, Bio-inspired method

Abstract

The faulty recovery of multi-robot system is an essential and challenging issue. Self-healing is one of the hot spots in the faulty recovery field. Recently, more and more bio-inspired methods have been proposed to deal with the self-healing problem. However, there are a lot of problems that should be studied further, such as the bio-inspired self-healing mechanism and the efficiency of the bio-inspired self-healing methods. In this paper, an improved bio-inspired self-healing method based on the immune-inspired swarm aggregation algorithm is proposed for multi-robot system, and the power shortage failure recovery is used as the concrete self-healing task. In the proposed approach, a hybrid algorithm of discrete particle swarm optimization (DPSO) algorithm and simulated annealing (SA) algorithm is presented, to choose the donor robots efficiently. In addition, an improved swarm aggregation algorithm based on fuzzy control is proposed to improve the concentration degree of multi-robot system in swarm aggregation process and maintain the stability of the multi-robot system in the self-healing process. Finally, some simulations are conducted, and the simulation results show that the proposed approach can complete the self-healing task effectively and efficiently.

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