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Found 2 papers, 1 papers with code
Not Only Rewards But Also Constraints: Applications on Legged Robot Locomotion
In this work, we propose a novel reinforcement learning framework for training neural network controllers for complex robotic systems consisting of both rewards and constraints.
Concurrent Training of a Control Policy and a State Estimator for Dynamic and Robust Legged Locomotion
In this paper, we propose a locomotion training framework where a control policy and a state estimator are trained concurrently.
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