基于人工免疫势场法的移动机器人路径规划
Path Planning of Mobile Robot Based on Artificial Immune Potential Field Algorithm
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摘要: 针对人工势场法和基本遗传算法在解决移动机器人的路径规划问题时。容易产生目标不可达和局部极小值的问题,提出了1种基于人工免疫势场法的移动机器人路径规划算法(MRPP-AIPF).该算法将初始抗体群动态分配为记忆保留单元和临时抗体单元,通过交叉、变异和遗忘等算子进行进化操作,使较优抗体较早生成,提高了算法的收敛能力和保持抗体群的多样性.仿真实验表明,MRPP-AIPF算法属有效路径规划算法.Abstract: The basic Artificial Potential Field (APF) and the basic Genetic Algorithm (GA) for path planning of the mobile robot gets into goals nonreachable and the local minimum value.The paper puts forward a novel algorithm for path planning of mobile robot based on artificial immune potential field algorithm (MRPP- AIPF).The algorithm divides dynamically initial antibody population into memory reservation unit and temporary antibody unit.Furthermore,it adopts cross,mutation and forgotten operators to improve convergence ability and remain diversity of antibody population.The simulation indicates that MRPP-AIPF is effective.