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Found 4 papers, 1 papers with code
Learn to Teach: Improve Sample Efficiency in Teacher-student Learning for Sim-to-Real Transfer
We implement variants of our methods, conduct experiments on the MuJoCo benchmark, and apply our methods to the Cassie robot locomotion problem.
Infer and Adapt: Bipedal Locomotion Reward Learning from Demonstrations via Inverse Reinforcement Learning
Enabling bipedal walking robots to learn how to maneuver over highly uneven, dynamically changing terrains is challenging due to the complexity of robot dynamics and interacted environments.
Integrated Task and Motion Planning for Safe Legged Navigation in Partially Observable Environments
This study proposes a hierarchically integrated framework for safe task and motion planning (TAMP) of bipedal locomotion in a partially observable environment with dynamic obstacles and uneven terrain.
Adversary A3C for Robust Reinforcement Learning
Asynchronous Advantage Actor Critic (A3C) is an effective Reinforcement Learning (RL) algorithm for a wide range of tasks, such as Atari games and robot control.
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