Multi-UAV Reconnaissance Task Allocation in 3D Urban Environments

This paper considers a reconnaissance task allocation problem for multiple unmanned aerial vehicles (UAVs) in 3D urban environments. In this paper, we present an extended heterogeneous targets reconnaissance task allocation model which introduced cuboid targets for 3D urban environment to improve th...

Full description

Saved in:
Bibliographic Details
Published in:IEEE access 2024-01, Vol.12, p.1-1
Main Authors: Tian, Xiangrui, Xu, Tong, Luo, Xin, Jia, Yinjun, Yin, Jie
Format: Article
Language:English
Subjects:
3D urban environment
Autonomous aerial vehicles
generalized multi-traveling salesman problem
np-hard problem
Optimization
Reconnaissance
Reconnaissance aircraft
Resource management
Search algorithms
Symbiosis
symbiotic organisms search
task allocation
Task analysis
Three-dimensional displays
Traveling salesman problem
unmanned aerial vehicle
Unmanned aerial vehicles
Urban areas
Urban environments
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper considers a reconnaissance task allocation problem for multiple unmanned aerial vehicles (UAVs) in 3D urban environments. In this paper, we present an extended heterogeneous targets reconnaissance task allocation model which introduced cuboid targets for 3D urban environment to improve the fidelity of the model. A reconnaissance method is designed for each type of target, and the mission is described as a heterogeneous target multi-traveling salesman problem model for solving complex optimization problems with multiple constraints.To address these complex optimization problems, multi-group symbiotic organisms search algorithms (MGSOS) are proposed, which maintain the diversity of species in the population through multi-group strategies and enhance information exchange between individuals in three stages. Real-number encoding is used to satisfy partial constraints and simplify the search space, improving the optimization efficiency of the solution. The simulation results show that the MGSOS algorithm can consider the characteristics of UAV sensor performance and heterogeneous targets. It outperforms the common symbiotic organisms search (SOS) algorithm in terms of the optimality of assignment results, and is suitable for larger scale urban reconnaissance task allocation problems.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2024.3368851