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• W4308695719 abstract "This paper proposes an evading strategy based on reinforcement learning for the pursuit-evasion problem considering hypersonic vehicle dynamics (evader) and multiple interceptors (pursuers). Analytical solutions are hard to obtain, so a reinforcement learning method is adopted for the vehicle’s guidance commands in evasion. To cast the problem to a Markov-Decision-Process (MDP), we first establish the motion model involves multiple pursuers and one evader. Moreover, we choose their positions, and velocities change in the three-dimensional space as the state transition, considering a proportional navigation interception guidance. Furthermore, the weighted sum of the zero-effort-miss perpendicular to line-of-sight and the magnitude of maneuver is chosen to be a reward function. After training using a PPO-Clip algorithm, a policy for evasion is obtained. Numerical experiments validate that the method we put forward can be used in the sequential evasion decision against multiple pursuers for a hypersonic vehicle." @default.
• W4308695719 created "2022-11-14" @default.
• W4308695719 creator A5015640756 @default.
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• W4308695719 date "2022-11-11" @default.
• W4308695719 modified "2023-10-05" @default.
• W4308695719 title "An evading strategy for hypersonic vehicle against multiple interceptors via reinforcement learning" @default.
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• W4308695719 doi "https://doi.org/10.1117/12.2641322" @default.
• W4308695719 hasPublicationYear "2022" @default.
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