Safe Reinforcement Learning With Stability Guarantee for Motion Planning of Autonomous Vehicles
IEEE Transactions on Neural Networks and Learning Systems(2021)
摘要
Reinforcement learning with safety constraints is promising for autonomous vehicles, of which various failures may result in disastrous losses. In general, a safe policy is trained by constrained optimization algorithms, in which the average constraint return as a function of states and actions should be lower than a predefined bound. However, most existing safe learning-based algorithms capture s...
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关键词
Autonomous vehicles,Planning,Safety,Stability criteria,Lyapunov methods,Trajectory,Robot sensing systems
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