Article: Mathematical modelling of multi-UAV scenario planning based on 3D LiDAR Journal: International Journal of Information and Communication Technology (IJICT) 2024 Vol.24 No.6 pp.1 - 22 Abstract: 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. Inderscience Publishers - linking academia, business and industry through research

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

Authors: Ruishuai Chai

Addresses: Henan Industry and Trade Vocational College, Zhengzhou 450046, China

Abstract: 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.

Keywords: 3D LiDAR; multi-UAV; scene planning; mathematical modelling.

DOI: 10.1504/IJICT.2024.138558

International Journal of Information and Communication Technology, 2024 Vol.24 No.6, pp.1 - 22

Received: 07 Nov 2023
Accepted: 11 Jan 2024
Published online: 12 May 2024 *

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

Keep up-to-date