Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications

Puze Liu; Haitham Bou Ammar; Jan Peters; Davide Tateo

doi:10.1109/tro.2025.3567477

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Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications

Puze Liu Haitham Bou Ammar Jan Peters Davide Tateo

Year: 2025 Journal: IEEE Transactions on Robotics Vol: 41 Pages: 3442-3461 Publisher: Institute of Electrical and Electronics Engineers

DOI: 10.1109/tro.2025.3567477

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Keywords:

Reinforcement learning Constraint (computer-aided design) Computer science Artificial intelligence Manifold (fluid mechanics) Mathematical optimization Mathematics Engineering Mechanical engineering Geometry

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Reinforcement Learning in Robotics

Physical Sciences → Computer Science → Artificial Intelligence

Scheduling and Optimization Algorithms

Physical Sciences → Engineering → Industrial and Manufacturing Engineering

Autonomous Vehicle Technology and Safety

Physical Sciences → Engineering → Automotive Engineering

Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications

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