首页> 外文会议>IEEE Chinese Guidance, Navigation and Control Conference >Multiple UAVs mission assignment based on modified Pigeon-inspired optimization algorithm
【24h】

Multiple UAVs mission assignment based on modified Pigeon-inspired optimization algorithm

机译:基于改进的Pigeon-Inspireat优化算法的多个无人机任务任务

获取原文

摘要

Unmanned aerial vehicles (UAVs) have shown their superiority for applications in performing military and civilian missions. In which, multiple UAVs mission assignment is becoming more important for today's military activities. So far, there have been many bio-inspired computation algorithms for solving multiple UAVs mission assignment problems, including particle swarm optimization (PSO), differential evolution algorithm (DE) and so on. However, deficiencies of these approaches exist inevitably, which cannot satisfy the requirements of dynamic mission assignment. In this paper, a new UAV assignment model focusing on the energy consumption of UAV is brought up which can be easily applied to intelligence algorithms. Meanwhile, we propose a new approach by applying the modified Pigeon-Inspired Optimization (PIO) algorithm to sovle the multiple UAVs mission assignment problem. The simulation results show that the modified PIO algorithm is more effective when compared with other state-of-the-art algorithms in addressing mission assignment problem for multiple UAVs.
机译:无人驾驶航空公司(无人机)对执行军事和平民任务的应用方面表现出优势。其中,对当今的军事活动变得越来越重要。到目前为止,已经有许多生物启发的计算算法来解决多个无人机任务分配问题,包括粒子群优化(PSO),差分演进算法(DE)等。然而,这些方法的缺陷不可避免地存在,这不能满足动态任务分配的要求。在本文中,提出了一种专注于UAV能量消耗的新UAV分配模型,可以很容易地应用于智能算法。同时,通过应用修改的鸽子启发优化(PIO)算法来解决多个无人机任务分配问题,提出了一种新的方法。仿真结果表明,与其他最先进的算法相比,修改的PIO算法更有效地解决了多个无人机的任务分配问题。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号