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基于改进蚁群算法的移动机器人平滑路径规划

  

  1. 石家庄铁道大学交通运输学院,河北 石家庄 050043
  • 出版日期:2019-04-30 发布日期:2019-05-10
  • 基金资助:
    河北省重点研发计划项目(18390324D);石家庄市科学技术研究与发展计划项目(181130034A,191260411A);石家庄铁道大学研究生创新 项目(YC2019044)

Smooth Path Planning of Mobile Robot Based on  Improved Ant Colony Algorithm

  1. School of Traffic and Transportation, Shijiazhuang Tiedao University, Shijiazhuang Hebei 050043, China
  • Online:2019-04-30 Published:2019-05-10

摘要: 针对移动机器人提出了基于改进蚁群算法的平滑路径规划方法。为了克服蚁群算 法解决路径规划问题时存在的收敛速度慢的缺点,对启发因子的矩阵初始值及更新方式进行了 改进,启发因子改进后的结果与之前相比,平均路径长度减少了 17.6%,平均收敛代数减少了 93.1%;对于栅格环境下存在障碍物时机器人累计转弯角度大的问题,提出了控制点转移策略, 在上一步改进的基础上,通过对控制路径走向的栅格中心点向栅格角顶点的转移,实现了路径 规划的平滑改进。路径规划仿真结果表明,与平滑改进前相比,平滑改进后机器人的平均路径 长度减少了 4.28%,累计转弯角度减少了 52.58%。

关键词: 蚁群算法, 移动机器人, 路径规划, 控制点转移策略

Abstract: A smooth path planning method based on improved ant colony algorithm is proposed for mobile robot in this paper. In order to overcome the disadvantage of slow convergence rate of ant colony algorithm in solving path planning problem, the initial value and updating method of the matrix of heuristic factors are improved. Compared with the results that the heuristic factor has not been improved, the average path length is reduced by 17.6%, and the average convergence algebra is decreased by 93.1%. The control point transfer strategy is proposed to solve the problem of large cumulative turning angle of the robot when obstacles exist in the grid environment. Based on the previous improvement, a smooth improvement of path planning is achieved by transferring the central point of grid to the vertex of grid. The path planning simulation results show that the average path length of the robot is decreased by 4.28% and the cumulative turning angle is reduced by 52.58%, compared with the non-smooth improvement.

Key words: ant colony algorithm, mobile robot, path planning, control point transfer strategy