Polyclonal based artificial immune network (PC-AIN) is utilized formobile robot path planning. Artificial immune network (AIN)\nhas been widely used in optimizing the navigation path with the strong searching ability and learning ability. However, artificial\nimmune network exists as a problem of immature convergence which some or all individuals tend to the same extreme value in\nthe solution space. Thus, polyclonal-based artificial immune network algorithm is proposed to solve the problem of immature\nconvergence in complex unknown static environment. Immunity polyclonal algorithm (IPCA) increases the diversity of antibodies\nwhich tend to the same extreme value and finally selects the antibody with highest concentration.Meanwhile, immunity polyclonal\nalgorithm effectively solves the problem of local minima caused by artificial potential field during the structure of parameter in\nartificial immune network. Extensive experiments show that the proposed method not only solves immature convergence problem\nof artificial immune network but also overcomes local minima problem of artificial potential field. So, mobile robot can avoid\nobstacles, escape traps, and reach the goal with optimum path and faster convergence speed.
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