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针对传统移动机器人路径规划方法存在的不足,基于独特型免疫网络理论,提出一种改进的免疫网络算法(MINA)用于移动机器人路径规划问题.该算法采用一种新的抗体对称均匀变异成熟机制和子群稳定判定策略,减少了算法对抗体克隆规模的过于敏感性,大大降低了算法的计算量;为真正体现免疫网络动态调节机制,增加抗体的多样性,提出了一种基于抗体亲和度和浓度的选择方法.仿真实验结果表明,该算法能使移动机器人在较复杂环境下快速找到一条优化路径,与同类算法相比具有一定优越性,是一种有效的移动机器人路径规划算法.
Aimed at the shortcomings of traditional mobile robot path planning methods, this paper proposes an improved Immune Network Algorithm (MINA) for mobile robot path planning based on the unique immune network theory. This algorithm uses a novel symmetric uniform mutation mature mechanism And the subgroup stability decision method, which reduces the sensitivity of the algorithm to the antibody cloning scale and greatly reduces the computational complexity of the algorithm. In order to truly reflect the dynamic regulation mechanism of the immune network and increase the diversity of the antibody, a method based on the antibody affinity And the concentration selection method.The simulation results show that the proposed algorithm can make mobile robot quickly find an optimized path in more complex environment and has certain advantages compared with other similar algorithms and it is an effective path planning algorithm for mobile robot.