基于改进遗传算法的移动机器人路径规划

标准遗传算法在解决各类优化问题中获得成功，但它在具体的应用中由于缺乏对特定知识的利用，其性能有待提高。将改进遗传算法用于移动机器人的全局路径规划，复杂的二维编码问题简化为一维编码问题，建立边界约束，路径点必须在障碍物之外，路径点连线不能与障碍物相交等3个约束条件，以机器人行走路径最短作为适应度函数进行遗传优化。计算机仿真实验结果证明该算法在收敛速度、最优解输出概率方面相对于基本遗传算法有了显著提高。

Enhanced Genetic Algorithm for Robotic Path Planning

Genetic algorithm has been very successful in solving optimization problems.However, due to the absence of utilizing specific knowledge of the particular context in which it is applied, its performance still requires improvements.A new approach of global path planning for mobile robot based on enhanced genetic algorithm is presented and the complex two dimension coding problem is converted into the one dimension ones. The restrictions on the boundary and the path node out of the obstacles and the restriction on the line between path nodes not crossing over the obstacles are put into .At the same time the fitness function meets the requirement of the shortest period of working length .The simulation results demonstrate that, the proposed algorithm achieved considerable improvements, with respect to the basic genetic algorithm,in convergence speed and optimal solution output rate.