Abstract
Abstract In this paper, a Reactive Immune Network (RIN) is proposed and employed for mobile robot navigation in unknown environments. Rather than building a detailed mathematical model of artificial immune systems, this study tries to explore the principle in an immune network focusing on its self-organization, adaptive learning capability, and immune feedback. In addition, an adaptive virtual target method is integrated to solve the local minima problem in navigation. Several trapping situations are adopted to evaluate the performance of the proposed architecture. Experimental results show that the mobile robot is capable of avoiding obstacles, escaping traps, and reaching the goal efficiently and effectively.
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