Collision-Free Maneuvering for a UAV Swarm Based on Parallel Control
The maneuvering of a large-scale unmanned aerial vehicle (UAV) swarm, notable for flexible flight with collision-free, is still challenging due to the significant number of UAVs and the compact configuration of the swarm. In light of this problem, a novel parallel control method that utilizes space and time transformation is proposed. First, the swarm is decomposed based on a grouping-hierarchical strategy, while the distinct flight roles are assigned to each UAV. Then, to achieve the desired configuration (DCF) in the real world, a bijection transformation is conducted in the space domain, converting an arbitrarily general configuration (GCF) into a standard configuration (SCF) in the virtual space. Further, to improve the flexibility of the swarm, the time scaling transformation is adopted in the time domain, which ensures the desired prescribed-time convergence of the swarm independent of initial conditions. Finally, simulation results demonstrate that collision-free maneuvering, including formation changes and turning, can be effectively and rapidly achieved by the proposed parallel control method. Overall, this research contributes a viable solution for enhancing cooperation among large-scale UAV swarms.
Authors
- Yangwang Fang (ORCID: https://orcid.org/0000-0002-1205-1513)
- Dengxiu Yu (ORCID: https://orcid.org/0000-0003-1803-3946)
- Wenhui Ma (ORCID: https://orcid.org/0000-0003-0109-3280)
- Jiacheng Li (ORCID: https://orcid.org/0009-0003-8235-5568)
- C. L. Philip Chen (ORCID: https://orcid.org/0000-0001-5451-7230)
Institutions
- Northwestern Polytechnical University (CN)
- University of Macau (MO)
- Xi'an Technological University (CN)
- South China University of Technology (CN)
Publication Details
- Journal
- IEEE/CAA Journal of Automatica Sinica
- Published
- 2025-03-31
- DOI
- https://doi.org/10.1109/jas.2024.124674
- Citations
- 10
- Primary Topic
- Robotic Path Planning Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 12.76
Funders
- National Natural Science Foundation of China