In this paper, first the immune system is analyzed in a relatively deeper and all-sided point of view reflecting the fresh research in biology. Second, based on the previous statements, a new optimization method, the immune genetic algorithm (IGA), is presented by simulating the behavior of the biological immune system and is proved to converge to the global optimum with probability 1. Third, a new method on the multi-object optimization that is transformed into a single-object one is proposed based on the joints' best compliance in the redundant robot path planning using IGA. Last, the experiment results show that the method of this article behaves more successfully.
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