计算机与现代化 ›› 2021, Vol. 0 ›› Issue (06): 1-5.

• 算法设计与分析 •    下一篇

基于改进鲸鱼优化算法的多无人机围捕

  

  1. (河海大学物联网工程学院,江苏常州213022)
  • 出版日期:2021-07-05 发布日期:2021-07-05
  • 作者简介:凌文通(1996—),男,安徽黄山人,硕士研究生,研究方向:无人机协同控制,目标围捕,E-mail: 1140205368@qq.com; 倪建军(1978—),男,安徽黄山人,教授,研究方向:机器人,人工智能,机器学习,E-mail: njjhhuc@gmail.com; 陈颜(1995—),男,广东潮洲人,博士研究生,研究方向:深度学习,机器人环境感知,E-mail: stcy401@126.com; 唐广翼(1997—),男,江苏徐州人,硕士研究生,研究方向:目标检测,图像处理,E-mail: tgy_hohai@163.com。
  • 基金资助:
    国家自然科学基金资助项目(61873086)

Multi-UAV Hunting Based on Improved Whale Optimization Algorithm

  1. (College of Internet of Things Engineering, Hohai University, Changzhou, 213022, China)
  • Online:2021-07-05 Published:2021-07-05

摘要: 无人机围捕是一项具有挑战性和现实意义的任务,为使无人机可以成功有效地围捕移动目标,提出一种基于动态预测围捕点和改进鲸鱼优化算法的多无人机围捕算法。在环境未知,目标运动轨迹未知的情况下,首先利用多项式拟合预测目标运动轨迹,通过动态预测步数得到预测点,在其周围设置围捕点,然后使用双向协商法为无人机合理分配各个目标点。针对鲸鱼优化算法容易陷入局部最优的缺点,提出基于自适应权重和改变螺旋线位置更新的方法,从而提升算法的开发能力和搜索能力。最终在不同实验环境下进行多次实验仿真,实验结果表明了所提出算法的有效性。

关键词: 动态预测, 目标围捕, 双向协商, 鲸鱼优化算法

Abstract: UAV hunting is a challenging and realistic task. In order to enable UAVs to hun moving targets successfully and effectively, a multi-UAV hunting algorithm based on dynamic prediction of hunting points and improved whale optimization algorithm is proposed. When the environment is unknown and the target motion trajectory is unknown, this paper first uses polynomial fitting to predict the target motion trajectory, obtains the prediction point by dynamically predicting the number of steps, sets up hunting points around it, and then uses the two-way negotiation method to make reasonable assign each target point. Aiming at the shortcomings of the whale optimization algorithm that it is easy to fall into the local optimum, a method based on adaptive weights and changing the position of the spiral is proposed to improve the development ability and search ability of the algorithm. Finally, several experimental simulations were carried out in different experimental environments, and the experimental results showed the effectiveness of the proposed algorithm.

Key words: dynamic prediction, target hunting, two-way negotiation, whale optimization algorithm