Affiliation:
1. School of Aeronautics and Astronautics, Zhejiang University, Hangzhou 310027, China
Abstract
Formation path planning is a significant cornerstone for unmanned aerial vehicle (UAV) swarm intelligence. Previous methods were not suitable for large-scale UAV formation, which suffered from poor formation maintenance and low planning efficiency. To this end, this paper proposes a novel millisecond-level path planning method appropriate for large-scale fixed-wing UAV formation, which consists of two parts. Instead of directly planning paths independently for each UAV in the formation, the proposed method first introduces a formation control strategy. It controls the chaotic UAV swarm to move as a single rigid body, so that only one planning can obtain the feasible path of the entire formation. Then, a computationally lightweight Dubins path generation method with a closed-form expression is employed to plan feasible paths for the formation. During flight, the aforementioned formation control strategy maintains the geometric features of the formation and avoids internal collisions within the formation. Finally, the effectiveness of the proposed framework is exemplified through several simulations. The results show that the proposed method can not only achieve millisecond-level path planning for the entire formation but also excellently maintain formation during the flight. Furthermore, simple formation obstacle avoidance in a special case also highlights the application potential of the proposed method.
Reference27 articles.
1. Rudol, P., and Doherty, P. (2008, January 1–8). Human Body Detection and Geolocalization for UAV Search and Rescue Missions Using Color and Thermal Imagery. Proceedings of the IEEE Aerospace Conference, Big Sky, MT, USA.
2. Supporting wilderness search and rescue using a camera-equipped mini UAV;Goodrich;J. Field Robot.,2008
3. Seeing the forest from drones: Testing the potential of lightweight drones as a tool for long-term forest monitoring;Zhang;Biol. Conserv.,2016
4. Scherer, J., and Rinner, B. (2016, January 21–25). Persistent multi-UAV surveillance with energy and communication constraints. Proceedings of the 2016 IEEE International Conference on Automation Science and Engineering (CASE), Fort Worth, TX, USA.
5. Anderson, B.D.O., Fidan, B., Yu, C., and Walle, D. (2008). Recent Advances in Learning and Control, Springer.
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