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08/25/2023
Learn With Imagination: Safe Set Guided State-wise Constrained Policy Optimization
Deep reinforcement learning (RL) excels in various control tasks, yet th...
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06/21/2023
State-wise Constrained Policy Optimization
Reinforcement Learning (RL) algorithms have shown tremendous success in ...
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05/23/2023
GUARD: A Safe Reinforcement Learning Benchmark
Due to the trial-and-error nature, it is typically challenging to apply ...
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04/18/2023
Hybrid Task Constrained Planner for Robot Manipulator in Confined Environment
Trajectory generation in confined environment is crucial for wide adopti...
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02/06/2023
State-wise Safe Reinforcement Learning: A Survey
Despite the tremendous success of Reinforcement Learning (RL) algorithms...
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01/24/2023
AutoCost: Evolving Intrinsic Cost for Zero-violation Reinforcement Learning
Safety is a critical hurdle that limits the application of deep reinforc...
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10/03/2022
Probabilistic Safeguard for Reinforcement Learning Using Safety Index Guided Gaussian Process Models
Safety is one of the biggest concerns to applying reinforcement learning...
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09/19/2022
Safety Index Synthesis via Sum-of-Squares Programming
Control systems often need to satisfy strict safety requirements. Safety...
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09/14/2022
Robust Safe Control for Uncertain Dynamic Models
Model mismatches prevail in real-world applications. Hence it is importa...
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04/18/2021
Provably Safe Tolerance Estimation for Robot Arms via Sum-of-Squares Programming
Tolerance estimation problems are prevailing in engineering applications...
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08/09/2020
Contact-Rich Trajectory Generation in Confined Environments Using Iterative Convex Optimization
Applying intelligent robot arms in dynamic uncertain environments (i.e.,...
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01/27/2020
Experimental Evaluation of Human Motion Prediction: Toward Safe and Efficient Human Robot Collaboration
Human motion prediction is non-trivial in modern industrial settings. Ac...
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10/01/2018
