Paper
27 November 2019 Research on autonomous maneuvering decision of UCAV based on approximate dynamic programming
Zhencai Hu, Peng Gao, Fei Wang
Author Affiliations +
Proceedings Volume 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence; 113212P (2019) https://doi.org/10.1117/12.2547893
Event: The Second International Conference on Image, Video Processing and Artifical Intelligence, 2019, Shanghai, China
Abstract
Unmanned aircraft systems can perform some more dangerous and difficult missions which manned aircraft systems cannot perform. For tasks with high complexity, such as air combat, maneuvering decision mechanism is required to sense the combat environment and make the optimal strategy in real time. This paper formulates one-to-one air combat maneuvering problem in 3D environment, and proposes an approximate dynamic programming approach to make optimal maneuvering decisions automatically. The aircraft searches for combat strategies based-on Reinforcement Leaning, while sensing the environment, taking available maneuvering actions and receiving feedback reward signals. To solve the problem of dimensional explosion in the air combat, the proposed method is implemented through feature selection, trajectory sampling, function approximation and Bellman backup operation in the air combat simulation environment. This approximate dynamic programming approach provides a fast response to rapid changing tactical situations, and learns effective strategies to fight against the opponent aircraft.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhencai Hu, Peng Gao, and Fei Wang "Research on autonomous maneuvering decision of UCAV based on approximate dynamic programming", Proc. SPIE 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence, 113212P (27 November 2019); https://doi.org/10.1117/12.2547893
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
Back to Top