关键词: 全局路径规划, 环境建模, 正反馈, 遗传算法

Abstract: Genetic Algorithm（GA） is applied to the global Robot Path Planning in this article.A novel modeling method is presented for GA for global robot path planning，which is implemented only dependent on the positions of the start node and the goal node of the robot.This method avoids the disadvantages of the complexity of the MAKLINK Graph modeling and the most popular Grid modeling method，such as the difficulty of allocating grid grain，the inconsistence of the chromosomes’ length and the complexity of calculation.Genes lie in the vertical lines of nodes that equally divide the line from the start node of the robot to the goal node，and are denoted in single value .To speed up the convergence of GA，the positive feedback from the Ant Colony Optimization（ACO） is introduced to the crossover operation and the mutation operation.The experiment results demonstrate this algorithm can immediately find a path even in complex environments.

Key words: global path planning, environment model, positive feedback, genetic algorithm