摘要
为了解决障碍物附近目标不可到达目的地问题,提出了一种融合算法用于移动机器人路径规划.融合算法对人工势场进行了改进,构造了新斥力势场函数,引入了指数因子,平衡了障碍物的斥力,从而消除了奇异值点,使机器人到达了目标点.然后利用量子遗传算法对最优或次优个体进行选择,为最优或次优个体进入下一代移动机器人提供了保障,提高了安全性、实现了路径的优化.仿真结果表明,融合算法能有效地提高路径规划的性能.
In order to solve goals non-reachable with obstacles nearby （GNRON）, a novel technology of mobile robot path planning based on a fusion algorithm is proposed. A new potential field function is presented by adding an exponential factor to the repulsive potential functions, it can balance the repulsive force of obstacles and eliminate singularity in planning, and the robot can get to the goal. QGA is used to select the optimal or sub-optimal path in order to protect the optimal or sub-optimal path into the next generation, and optimization of the route length and safety are realized. Simulation result shows that the proposed method can effectively improve the performance of path planning.
出处
《商丘职业技术学院学报》
2015年第5期25-28,共4页
JOURNAL OF SHANGQIU POLYTECHNIC
关键词
势场法
路径规划
移动机器人
量子遗传算法
potential field
path Planning
mobile robot
quantum genetic algorithm （QGA）
