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中文摘要：
将一种自适应遗传算法应用于移动机器人路径规划．提出了一种基于几何避障法的初始种群产生算法；设计了基于启发式知识的交叉、变异、求精和删除算子；采用一种新的模糊逻辑控制算法自适应地调节交叉概率和变异概率；对移动机器人离线和在线规划问题进行了仿真研究．仿真结果表明：自适应遗传算法具有较快的搜索速度、较高的搜索质量以及较强的自适应能力，为移动机器人最优路径规划问题的解决提供了一种新方法．
英文摘要：
An adaptive genetic algorithm for the optimum path planning problem of a mobile robot was proposed. The research project was carried out from four aspects： a geometry obstacle avoiding algorithm was developed to generate initial population; the crossover, mutation, improving and deletion operators which base on heuristic knowledge were designed for path planning; a new kind of fuzzy logic control algorithm was adopted to self-adaptively adjust the probabilities of crossover and mutation; simulation studies in both off-line and on-line environments were implemented. The simulation results show that the adaptive genetic algorithm has advantages such as rapid search speed, high search quality and strong self-adaptability. It is a new approach for solving the optimum path planning problem of a mobile robot.
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