Multi-UAV autonomous formation task is one of the important research hotspots in UAV application. A typical mission scenario is constructed for the autonomous formation, maintenance and obstacle avoidance tasks of multi-UAV. Based on Multiple-Agents Deep Deterministic Policy Gradient (MADDPG) algorithm, we designed a hybrid reward distribution mechanism for autonomous formation task, which effectively solved the problem of uneven global reward distribution and individual "selfish strategy", and designed a dynamic communication strategy inside the UAV formation to reduce the computational complexity. It can effectively improve the communication efficiency between UAVs. After training, the UAV can effectively avoid the no-fly zone and efficiently perform autonomous formation flight task. The introduction of the hybrid reward mechanism improves the stability of the UAV autonomous formation task and has certain application prospects.
Research on autonomous formation of Multi-UAV based on MADDPG algorithm
27.06.2022
1264178 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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