学术论文

      一种基于遗传算法参数优化的改进人工势场法

      An improved artificial potential field method with parameters optimization based on genetic algorithms

      摘要:
      人工势场法是一种简单有效的移动机器人路径规划算法.针对传统人工势场法在路径规划中的一类目标点不可达问题,提出了一种在局部最小点改变斥力角度和设定虚拟最小局部区域的解决方案,同时采用遗传算法对改进算法中斥力改变角度以及虚拟最小局部区域的半径两个参数进行优化.仿真实验说明本文所提算法能在起点和终点之间规划出一条简捷、光滑和安全的路径.
      Abstract:
      The artificial potential field method is a simple and efficient path planning algorithm for mobile robots.Aiming at a kind of goal unreachable problem in traditional artificial potential field methods,an improved algorithm which changes the angle of repulsion at the local minimum point and sets the virtual local minimum area was proposed for problem-solving.The genetic algorithm was also introduced to optimize the parameters,i.e.the revolved angle of repulsion and the radius of the virtual local minimum area for the improved artificial potential field algorithm.It is proved that the proposed algorithm can plan out a simple,smooth and safe optimum path connecting the start point and the end point by simulation experiments.
      作者单位: 北京科技大学自动化学院,北京,100083
      刊 名: 北京科技大学学报 ISTICEIPKU
      年,卷(期): 2012, 34(2)
      分类号: TP242.6
      机标分类号: TS1 TH1
      在线出版日期: 2012年4月28日
      基金项目: 教育部第36批"留学回国人员科研启动基金"资助项目,国家自然科学基金资助项目,北京市重点学科建设资助项目