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 20 条
[1]  
Baca T., Petrlik M., Vrba M., Spurny V., Penicka R., Hert D., Saska M., The MRS UAV system: pushing the frontiers of reproducible research, real-world deployment, and education with autonomous unmanned aerial vehicles, Journal of Intelligent & Robotic Systems, 102, 1, pp. 1-28, (2021)
[2]  
Basiri A., Mariani V., Silano G., Aatif M., Iannelli L., Glielmo L., A survey on the application of path-planning algorithms for multi-rotor UAVs in precision agriculture, The Journal of Navigation, 75, 2, pp. 364-383, (2022)
[3]  
Batinovic A., Petrovic T., Ivanovic A., Petric F., Bogdan S., A multi-resolution frontier-based planner for autonomous 3D exploration, IEEE Robotics and Automation Letters, 6, 3, pp. 4528-4535, (2021)
[4]  
Choi Y., Chen M., Choi Y., Briceno S., Mavris D., Multi-UAV trajectory optimization utilizing a NURBS-based terrain model for an aerial imaging mission, Journal of Intelligent & Robotic Systems, 97, 1, pp. 141-154, (2020)
[5]  
Choi Y.J., Ramatryana I.N.A., Shin S.Y., Cellular communication-based autonomous UAV navigation with obstacle avoidance for unknown indoor environments, International Journal of Intelligent Engineering and Systems, 14, 2, pp. 344-352, (2021)
[6]  
Hongming S.H.E.N., Qun Z.O.N.G., Hanchen L.U., Zhang X., Bailing T.I.A.N., Lei H.E., A distributed approach for LiDAR-based relative state estimation of multi-UAV in GPS-denied environments, Chinese Journal of Aeronautics, 35, 1, pp. 59-69, (2022)
[7]  
Kratky V., Petracek P., Baca T., Saska M., An autonomous unmanned aerial vehicle system for fast exploration of large complex indoor environments, Journal of Field Robotics, 38, 8, pp. 1036-1058, (2021)
[8]  
Le T., Gjevestad J.G.O., From P.J., Online 3D mapping and localization system for agricultural robots, IFAC-PapersOnLine, 52, 30, pp. 167-172, (2019)
[9]  
Miao Y., Tang Y., Alzahrani B.A., Barnawi A., Alafif T., Hu L., Airborne LiDAR assisted obstacle recognition and intrusion detection towards unmanned aerial vehicle: architecture, modeling and evaluation, IEEE Transactions on Intelligent Transportation Systems, 22, 7, pp. 4531-4540, (2020)
[10]  
Petracek P., Kratky V., Petrlik M., Baca T., Kratochvil R., Saska M., Large-scale exploration of cave environments by unmanned aerial vehicles, IEEE Robotics and Automation Letters, 6, 4, pp. 7596-7603, (2021)