计算机工程与应用 ›› 2019, Vol. 55 ›› Issue (20): 192-196.DOI: 10.3778/j.issn.1002-8331.1904-0212

• 工程与应用 • 上一篇    下一篇

基于改进蚁群算法的三维路径规划

陈超,张莉   

  1. 1.内江师范学院 四川省数据恢复重点实验室,四川 内江 641110
    2.内江师范学院 四川省高等学校数值仿真重点实验室,四川 内江 641110
  • 出版日期:2019-10-15 发布日期:2019-10-14

Three-Dimensional Path Planning Based on Improved Ant Colony Algorithm

CHEN Chao, ZHANG Li   

  1. 1.Data Recovery Key Laboratory of Sichuan Province, Neijiang Normal University, Neijiang, Sichuan 641110, China
    2.Key Laboratory of Numerical Simulation of Sichuan Province, Neijiang Normal University, Neijiang, Sichuan 641110, China
  • Online:2019-10-15 Published:2019-10-14

摘要: 针对移动机器人在海水环境中的三维路径规划问题容易陷入局部最优和收敛慢等瑕疵,根据三维环境全局信息来改进蚁群算法以提高实时性和收敛速度。改进蚁群算法的启发函数,采用局部信息和全局信息结合动态地改进信息素更新方式,以及根据三维空间中路径的平坦程度和光滑度二阶微分分别增加了一阶微分和二阶微分来再次修改信息素更新规则。仿真对比实验结果显示改进后的蚁群算法克服了收敛速度慢、容易陷入局部最优的缺点。

关键词: 移动机器人, 三维路径规划, 改进蚁群算法, 启发函数修改规则, 信息素更新规则

Abstract: In order to solve the problem of three-dimensional(3D) path planning for mobile robots in seawater environment, which is easy to fall into local optimum and slow convergence, ant colony algorithm is improved based on the global information of 3D environment to improve real-time performance and convergence speed. The heuristic function of ant colony algorithm is improved, and the pheromone updating method is dynamically improved by combining local information with global information. The pheromone updating rules are modified again by adding first-order and second-order differentials according to the flatness and smoothness of paths in 3D space. The simulation results show that the improved ant colony algorithm overcomes the shortcomings of slow convergence speed and is easy to fall into local optimum in solving the seawater 3D path planning problem.

Key words: mobile robot, three-dimensional path planning, improved ant colony algorithms, heuristic function modification rules, pheromone updating rules