Associate/Assistant Professor in Artificial Intelligence for Space-Enabled Technologies, Durham University

We are looking for applicants in Artificial Intelligence, Computer Vision, Edge Computing, Digital Twins, Human Computer Interaction, User Modelling, Robotics or Resilient Computing with potentials/achievements in informing space applications.

The post hoder will enjoy 1) a permanent (equivalent to US tenured) position at a top 100 university, 2) significantly reduced teaching, 3) a fully-funded PhD, 4) travel budget, 5) chance for a 2-year fully-funded Post-Doc.

Formation Control for UAVs Using a Flux Guided Approach

John Hartley, Hubert P. H. Shum, Edmond S. L. Ho, He Wang and Subramanian Ramamoorthy
Expert Systems with Applications (ESWA), 2022

 Impact Factor: 8.5 Top 25% Journal in Computer Science, Artificial Intelligence#

Formation Control for UAVs Using a Flux Guided Approach


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 seconds and 0.88 seconds, 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.





 author={Hartley, John and Shum, Hubert P. H. and Ho, Edmond S. L. and Wang, He and Ramamoorthy, Subramanian},
 journal={Expert Systems with Applications},
 title={Formation Control for UAVs Using a Flux Guided Approach},


AU  - Hartley, John
AU  - Shum, Hubert P. H.
AU  - Ho, Edmond S. L.
AU  - Wang, He
AU  - Ramamoorthy, Subramanian
T2  - Expert Systems with Applications
TI  - Formation Control for UAVs Using a Flux Guided Approach
PY  - 2022
SP  - 117665
EP  - 117665
DO  - 10.1016/j.eswa.2022.117665
SN  - 0957-4174
PB  - Elsevier
ER  - 

Plain Text

John Hartley, Hubert P. H. Shum, Edmond S. L. Ho, He Wang and Subramanian Ramamoorthy, "Formation Control for UAVs Using a Flux Guided Approach," Expert Systems with Applications, pp. 117665, Elsevier, 2022.

Supporting Grants

The Ministry of Defence (DASA)
D-FOCUS: Drone-FOrmation Control for countering future Unmanned aerial Systems
Defence and Security Accelerator (Ref: DSTLX-1000140725, ACC6007422): £124,901, Principal Investigator ()
Received from The Ministry of Defence (DASA), UK, 2019-2020
Project Page

Similar Research

Shoujiang Xu, Edmond S. L. Ho and Hubert P. H. Shum, "A Hybrid Metaheuristic Navigation Algorithm for Robot Path Rolling Planning in an Unknown Environment", Mechatronic Systems and Control (MSC), 2019



Last updated on 17 February 2024
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