Skip to main content

Research Repository

Advanced Search

Formation Control for UAVs Using a Flux Guided Approach

Hartley, John; Shum, Hubert P.H.; Ho, Edmond S.L.; Wang, He; Ramamoorthyd, Subramanian

Formation Control for UAVs Using a Flux Guided Approach Thumbnail


Authors

John Hartley

Edmond S.L. Ho

He Wang

Subramanian Ramamoorthyd



Abstract

Existing studies on formation control for unmanned aerial vehicles (UAV) have not considered encircling targets where an optimum coverage of the target is required at all times. Such coverage plays a critical role in many real-world applications such as tracking hostile UAVs. This paper proposes a new path planning approach called the Flux Guided (FG) method, which generates collision-free trajectories for multiple UAVs while maximising the coverage of target(s). Our method enables UAVs to track directly toward a target whilst maintaining maximum coverage. Furthermore, multiple scattered targets can be tracked by scaling the formation during flight. FG is highly scalable since it only requires communication between sub-set of UAVs on the open boundary of the formation’s surface. Experimental results further validate that FG generates UAV trajectories 1.5x shorter than previous work and that trajectory planning for 9 leader/follower UAVs to surround a target in two different scenarios only requires 0.52 s and 0.88 s, respectively. The resulting trajectories are suitable for robotic controls after time-optimal parameterisation; we demonstrate this using a 3d dynamic particle system that tracks the desired trajectories using a PID controller.

Citation

Hartley, J., Shum, H. P., Ho, E. S., Wang, H., & Ramamoorthyd, S. (2022). Formation Control for UAVs Using a Flux Guided Approach. Expert Systems with Applications, 205, Article 117665. https://doi.org/10.1016/j.eswa.2022.117665

Journal Article Type Article
Acceptance Date May 27, 2022
Online Publication Date Jun 9, 2022
Publication Date Nov 1, 2022
Deposit Date May 31, 2022
Publicly Available Date Aug 1, 2022
Journal Expert Systems with Applications
Print ISSN 0957-4174
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 205
Article Number 117665
DOI https://doi.org/10.1016/j.eswa.2022.117665

Files







You might also like



Downloadable Citations