Mathematical modelling of multi-UAV scenario planning based on 3D LiDAR

被引:0
|
作者
Chai R. [1 ]
机构
[1] Henan Industry and Trade Vocational College, Zhengzhou
关键词
3D LiDAR; mathematical modelling; multi-UAV; scene planning;
D O I
10.1504/IJICT.2024.138558
中图分类号
学科分类号
摘要
In order to improve the operation efficiency of multi-UAV groups, this paper studies the mathematical modelling of multi-UAV scene planning, takes 3D LiDAR technology as the base navigation technology, and uses the bacterial foraging algorithm as the multi-objective optimisation algorithm. Moreover, this paper appropriately improves the defects of the algorithm, and introduces the bacterial population in the algorithm into the log-linear model to improve the two basic behaviours of the algorithm, the trend and the migration, so that the local search of the algorithm is more accurate. In addition, this paper introduces Gauss-Cauchy variation to ensure the diversity of bacterial populations and ensure that the algorithm results are close to the global optimal value. Through experimental research, it is known that the algorithm proposed in this paper can drive the drone to conform to the flight trajectory as a whole, achieve the expected fusion positioning accuracy, and meet the requirements of autonomous cruising. The average registration time is 120 milliseconds, which meets the real-time perception of the scene and pose estimation requirements during cruising. The experimental study shows that the multi-UAV scene planning method based on 3D LiDAR can effectively improve the optimal control effect of multi-UAV. Copyright © The Author(s) 2024. Published by Inderscience Publishers Ltd. This is an Open Access Article distributed under the CC BY-NC-ND license. (http://creativecommons.org/licenses/by-nc-nd/4.0/)
引用
收藏
相关论文
共 50 条
  • [31] 3D Multi-UAV Computing Networks: Computation Capacity and Energy Consumption Tradeoff
    Xu, Yu
    Zhang, Tiankui
    Liu, Yuanwei
    Yang, Dingcheng
    Xiao, Lin
    Tao, Meixia
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2024, 73 (07) : 10627 - 10641
  • [32] Cooperative Formation and Obstacle Avoidance Algorithm for Multi-UAV System in 3D Environment
    Lin, Qianyu
    Wang, Xiaoli
    Wang, YuTong
    2018 37TH CHINESE CONTROL CONFERENCE (CCC), 2018, : 6943 - 6948
  • [33] Lidar on small UAV for 3D mapping
    Tulldahl, H. Michael
    Larsson, Hakan
    ELECTRO-OPTICAL REMOTE SENSING, PHOTONIC TECHNOLOGIES, AND APPLICATIONS VIII; AND MILITARY APPLICATIONS IN HYPERSPECTRAL IMAGING AND HIGH SPATIAL RESOLUTION SENSING II, 2014, 9250
  • [34] Robust multi-UAV route planning considering UAV failure
    Patel, Ruchir
    Rudnick-Cohen, Eliot
    Azarm, Shapour
    Herrmann, Jeffrey W.
    2019 INTERNATIONAL CONFERENCE ON UNMANNED AIRCRAFT SYSTEMS (ICUAS' 19), 2019, : 205 - 212
  • [35] Control of a multi-UAV system in string-like flight in 3D space
    Arogeti, Shai
    Ailon, Amit
    2023 INTERNATIONAL CONFERENCE ON UNMANNED AIRCRAFT SYSTEMS, ICUAS, 2023, : 40 - 47
  • [36] 3D Network Design for Multi-UAV RAN With THz-Empowered Backhaul
    Kim, Kyeongsoo
    Choi, Jihwan P.
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2024, 23 (11) : 16437 - 16452
  • [37] A Path Planning Method for Multi-UAV System
    Marro, Alessandro Assi
    Garcia Goncalves, Luiz Marcos
    2013 IEEE LATIN AMERICAN ROBOTICS SYMPOSIUM (LARS 2013), 2013, : 129 - 135
  • [38] Multi-UAV Path Planning Algorithm Based on BINN-HHO
    Li, Sen
    Zhang, Ran
    Ding, Yuanming
    Qin, Xutong
    Han, Yajun
    Zhang, Huiting
    SENSORS, 2022, 22 (24)
  • [39] MDP-Based Mission Planning for Multi-UAV Persistent Surveillance
    Jeong, Byeong-Min
    Ha, Jung-Su
    Choi, Han-Lim
    2014 14TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS 2014), 2014, : 831 - 834
  • [40] Reinforcement Learning Based Trajectory Planning for Multi-UAV Load Transportation
    Estevez, Julian
    Manuel Lopez-Guede, Jose
    del Valle-Echavarri, Javier
    Grana, Manuel
    IEEE ACCESS, 2024, 12 : 144009 - 144016