Coupled Optimization of UAV Cluster Path Optimization and Task Assignment on a Mobile Platform

This paper focuses on the coupled optimization problem of path optimization and task assignment for UAVs mounted on mobile platforms. Combining the UAV turning angle, minimum direct flight trajectory and other flight characteristics, the path optimization model on the 3D raster map is established with the objectives of shortest flight time and minimum UAV destruction, and the optimal path between the vertices of each mission is derived by using an improved Gray Wolf Optimization algorithm. Combining the takeoff and landing time-window constraints with the range and mission resource constraints, this mission planning model is established with the objective of maximizing the efficiency ratio of mission revenue–UAV damage consumption. Combining the optimal paths between vertices, a complete UAV flight path is formed, which provides a path optimization and goal assignment method for UAV clusters mounted on mobile platforms to perform multiple tasks cooperatively, and its feasibility and effectiveness are verified through simulation experiments.

Authors

Institutions

Publication Details

Journal
Mathematics
Published
2024-12-25
DOI
https://doi.org/10.3390/math13010027
Citations
1
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.25
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Coupled Optimization of UAV Cluster Path Optimization and Task Assignment on a Mobile Platform

Yanjie Wu, Guangtao Fu, Yexin Song
1 citations
Mathematics
Robotic Path Planning Algorithms
0.25
article

Coupled Optimization of UAV Cluster Path Optimization and Task Assignment on a Mobile Platform

Yanjie Wu, Guangtao Fu, Yexin Song
article en
1 citations

Abstract

This paper focuses on the coupled optimization problem of path optimization and task assignment for UAVs mounted on mobile platforms. Combining the UAV turning angle, minimum direct flight trajectory and other flight characteristics, the path optimization model on the 3D raster map is established with the objectives of shortest flight time and minimum UAV destruction, and the optimal path between the vertices of each mission is derived by using an improved Gray Wolf Optimization algorithm. Combining the takeoff and landing time-window constraints with the range and mission resource constraints, this mission planning model is established with the objective of maximizing the efficiency ratio of mission revenue–UAV damage consumption. Combining the optimal paths between vertices, a complete UAV flight path is formed, which provides a path optimization and goal assignment method for UAV clusters mounted on mobile platforms to perform multiple tasks cooperatively, and its feasibility and effectiveness are verified through simulation experiments.

MathematicsVol. 13(1)
Naval University of Engineering (CN)
Openalex Percentile: Top 43%
Robotic Path Planning Algorithms
0.25
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Coupled Optimization of UAV Cluster Path Optimization and Task Assignment on a Mobile Platform — Yanjie Wu, Guangtao Fu, et al. · Mathematics (2024) | TGRS Research Map | TGRS