TY - GEN
T1 - Research on autonomous maneuvering decision of UCAV based on approximate dynamic programming
AU - Hu, Zhencai
AU - Gao, Peng
AU - Wang, Fei
N1 - Publisher Copyright:
© 2019 SPIE.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Air Combat
KW - Approximate Dynamic Programming
KW - Maneuvering Decision
KW - Reinforcement Learning
UR - https://www.scopus.com/pages/publications/85077819745
U2 - 10.1117/12.2547893
DO - 10.1117/12.2547893
M3 - 会议稿件
AN - SCOPUS:85077819745
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - 2019 International Conference on Image and Video Processing, and Artificial Intelligence
A2 - Su, Ruidan
PB - SPIE
T2 - 2019 2nd International Conference on Image and Video Processing, and Artificial Intelligence, IVPAI 2019
Y2 - 23 August 2019 through 25 August 2019
ER -