Abstract:

Aiming at the shortcomings of existing genetic algorithm in solving robot path planning, such as slow convergence speed and easy to fall into local optimum, this paper proposes a robot path planning method based on adaptive genetic algorithm. This method introduces a reversal operator, adds an insert operator and a delete operator, and proposes a new adaptive strategy to adjust the crossover and mutation probabilities to better avoid falling into the local optimum and improve the efficiency of algorithm optimization. The algorithm is verified by examples in MATLAB and Inte3D platform. The experimental results show that the improved adaptive genetic algorithm is more effective than the existing genetic algorithms.

Key words: robot, path planning, adaptive genetic algorithm, genetic algorithm

摘要：

针对现有遗传算法在求解机器人路径规划存在的收敛速度慢、易陷入局部最优等缺点，提出一种基于自适应遗传算法的机器人路径规划方法。该方法引入逆转算子，增加插入算子和删除算子，提出新的自适应策略对交叉和变异概率进行调整，更好地避免陷入局部最优，提高算法寻优效率。该算法在MATLAB和Inte3D平台中进行算例验证，实验结果表明改进的自适应遗传算法比现有遗传算法更为有效。

关键词: 机器人, 路径规划, 自适应遗传算法, 遗传算法