移动机器人的路径规划是机器人研究的重要领域。文中旨在研究遗传算法对于机器人路径规划问题的适用性。对于路径规划的目标，提出了基于路径长度、路径平滑度和路径安全度等因素综合衡量的方法，并在传统的遗传算法的交叉、变异操作的基础上，针对路径规划问题的特点，增加了捷径寻找、障碍避让、平滑优化等方法。实验表明，此算法在存在形状复杂的障碍物的静态环境中表现良好，其效率与准确性皆满足机器人路径规划的要求。%Path planning is an important subject in mobile robot research area. It aims to verify the feasibility of genetic algorithm towards mobile robot path planning problem. The goal of path planning is measured by the combination of path length,path smoothness and path safety. Besides traditional operators of crossover and mutation in genetic algorithm,there are additional methods such as shortcut seeking, obstacle avoidance and smoothness optimization. Through experiments,the algorithm performs well in static environment with obstacles in complex shapes and its efficiency and accuracy satisfies the requirements of the problem.
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