基于二重势函数法的集群航路规划
Cluster path planning based on double potential fields
摘要点击 161  全文点击 71  投稿时间:2020-05-11  修订日期:2020-07-19
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DOI编号  10.7641/CTA.2020.00264
  2021,38(1):90-102
中文关键词  集群  形成构型  航路规划  无谓避碰  改进势场法  二重势能场
英文关键词  cluster  configuration formation  path planning  unnecessary collision avoidance  improved artificial potential field  double potential fields
基金项目  国家自然科学基金项目(61374186), 装发共用技术预研基金项目(315055302).
作者单位E-mail
陈天德 南京理工大学 自动化学院 369253482@qq.com 
黄炎焱 南京理工大学 自动化学院 huangyy@njust.edu.cn 
李琛 南京理工大学 自动化学院  
中文摘要
      人工势场法由于其在构型组织能力上的不足, 影响了该方法在集群航路规划上的应用, 为此提出基于二重 势函数法的集群航路规划法, 通过第一重势能场形成集群到目标的可行路径, 通过第二重势能场形成构型, 从而实 现集群航路规划. 此外, 针对人工势场法存在无谓避碰、陷阱问题等不足, 通过引入碰撞危险度来确定障碍物影响 距离以及虚拟障碍物, 提出改进的人工势场法. 所有改进措施均未改变简单且易于执行的传统势函数模型, 为采用 人工势场法实现集群航路规划提供了一种思路. 仿真结果表明改进的人工势场法很好的克服了不足, 所得路径也 较为平滑, 且以该方法为基础所构成的集群航路规划法在集群航路规划上具有较好的表现.
英文摘要
      The application of the artificial potential field method in cluster path planning is affected by the lack of configuration organization ability. Hence, this paper proposes a cluster path planning method based on double potential fields. Specifically, the feasible path to the target is formed by the first potential field and the cluster configuration is formed by the second potential field, which finally fulfill cluster path planning. Moreover, for the shortcomings of artificial potential field, such as unnecessary collision avoidance and trap problem, an improved artificial potential field method is proposed by introducing the collision risk to determine the influence distance of obstacles and the virtual obstacle method. All the improvements have not changed the traditional potential function model, which is simple and easy to implement, and this paper provide an idea for cluster path planning using the artificial potential field method. The simulation results show that the improved artificial potential field method overcomes the shortcomings well, and the obtained path is relatively smooth. Besides, the cluster path planning method based on this method has a better performance in cluster path planning.