基于改进遗传算法的机器人路径规划与仿真

针对标准遗传算法解决机器人处于障碍环境下寻找最优路径局部寻优精度较差、规划效率低的问题，提出一种改进遗传算法的机器人路径规划方法。该算法采用一维编码表示路径, 构造了路径最优化的目标函数和适应度函数，利用多个种群拓宽搜索空间，提高了规划效率,采用保优选择策略，避免陷入局部最优。仿真结果表明，改进遗传算法比标准遗传算法路径规划质量高，能够获得平滑的低代价路径，稳定性好，是机器人路径规划的一种较好的方法，且具有一定的推广意义。

ROBOT Route Planning and Simulation Based on Improved Genetic Algorithm

In order to improve the survivability of robot, and to overcome the poor ability at local searching precision and stabilization of the simple genetic algorithm, this paper proposed an improved genetic algorithm about route planning. The route was denoted by one-dimension coding, and the objective function and the fitness function of the route planning problem were constructed. It adopted multi-population to broaden search scope, and chose best for better efficiency. The simulation results show that the improved genetic algorithm has higher efficiency and stabilization than simple genetic algorithm, and it can also gain smooth and low cost route.