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Social-class pigeon-inspired optimization and time stamp segmentation for multi-UAV cooperative path planning

机译:社交级鸽子启发式优化和时间戳分割,用于多无人机协作路径规划

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摘要

Path planning is a significant issue for the safe flight of unmanned aerial vehicles (UAVs). In the situation of multiple UAVs, the problem is even more challenging due to the tough manipulation of coordination and constrains. In this paper, a novel multi-UAV path planning model is developed which is based on the time stamp segmentation (TSS) technique. Other than the traditional methods, the TSS model utilizes the common time bases to simplify the handling of multi-UAV coordination cost. Then, a novel social-class pigeon-inspired optimization (SCPIO) algorithm is proposed as the solver of optimal search on the TSS model. The social-class strategy is utilized to enhance the convergence capabilities of the standard PIO. The efficiency of the proposed method is verified through the comparative experiments and the performance profiles (PP). Integrated experiment in a 3D environment demonstrates the reliability of the proposed system. (C) 2018 Elsevier B.V. All rights reserved.
机译:路径规划是无人飞行器(UAV)安全飞行的重要问题。在多架无人机的情况下,由于对协调和约束的艰难操纵,问题甚至更具挑战性。本文基于时间戳分割(TSS)技术,开发了一种新型的多无人机路径规划模型。除传统方法外,TSS模型还利用通用时基来简化多无人机协调成本的处理。然后,提出了一种新的社交类鸽子启发优化算法(SCPIO)作为TSS模型最优搜索的求解器。社会阶层战略被用来增强标准PIO的融合能力。通过对比实验和性能曲线(PP)验证了所提方法的效率。在3D环境中的集成实验证明了所提出系统的可靠性。 (C)2018 Elsevier B.V.保留所有权利。

著录项

  • 来源
    《Neurocomputing》 |2018年第3期|229-246|共18页
  • 作者

    Zhang Daifeng; Duan Haibin;

  • 作者单位
  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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