北京航空航天大学学报 ›› 2021, Vol. 47 ›› Issue (2): 359-365.doi: 10.13700/j.bh.1001-5965.2020.0198

• 论文 • 上一篇    下一篇

基于鸽群优化算法的实时避障算法

李霜琳, 何家皓, 敖海跃, 刘燕斌   

  1. 南京航空航天大学 航天学院, 南京 210016
  • 收稿日期:2020-05-20 发布日期:2021-03-08
  • 通讯作者: 刘燕斌 E-mail:liuyb@nuaa.edu.cn
  • 作者简介:李霜琳,女,硕士研究生。主要研究方向:导航制导与控制;何家皓,女,硕士研究生。主要研究方向:高超声速飞行控制、飞行器复杂建模与控制;敖海跃,男,本科。主要研究方向:导航制导与控制;刘燕斌,男,博士,副教授,硕士生导师。主要研究方向:高超声速飞行控制、飞行器复杂建模与控制。

Real-time obstacle avoidance algorithm based on pigeon-inspired optimization

LI Shuanglin, HE Jiahao, AO Haiyue, LIU Yanbin   

  1. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Received:2020-05-20 Published:2021-03-08

摘要: 为保证机器人能安全无碰撞地抵达目标位置,提出一种在改进版圆形扩张(CSE+)法中融合鸽群优化算法的实时避障算法。所提算法引入对障碍物密集程度的判断机制,在障碍分布密集时选择最安全的路径,在障碍物分布稀松的环境中,利用鸽群优化算法在安全范围内寻找下一目标最优位置。此外,还引入了搜索树,可实现死角的检测与避免。仿真结果显示:所提避障算法能提高路径规划的性能,在障碍物分布稀松时效果更加明显,且可实现死角检测并能通过狭长通道。

关键词: 路径规划, 局部路径规划, 鸽群优化算法, 改进版圆形扩张(CSE+)法, 避障

Abstract: In order to ensure that the mobile robot can reach the target position without collisions, this paper proposes a real-time obstacle avoidance algorithm that integrates the pigeon-inspired optimization into the Circle Sector Expansion plus (CSE+) method. This algorithm includes a judgment mechanism to evaluate the distribution of obstacles. When the obstacles are densely distributed, the safest path will be selected. Otherwise, the pigeon-inspired optimization will be used to find an optimal position as the next target position in the safe range. In addition, a search tree is used to detect and avoid the dead-end situation. The simulation results show that this algorithm can improve the efficiency of path planning, the effect is more obvious when the obstacles are sparsely distributed, the dead-end situation can be detected, and the robot can pass through the narrow and long corridors.

Key words: path planning, local path planning, pigeon-inspired optimization algorithm, Circle Sector Expansion plus (CSE+) method, obstacle avoidance

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