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Found 3 papers, 1 papers with code
Sim-to-Real Learning for Bipedal Locomotion Under Unsensed Dynamic Loads
We show that prior RL policies trained for unloaded locomotion fail for some loads and that simply training in the context of loads is enough to result in successful and improved policies.
Iterative Reinforcement Learning Based Design of Dynamic Locomotion Skills for Cassie
Deep reinforcement learning (DRL) is a promising approach for developing legged locomotion skills.
Robotics
Reinforcement learning for non-prehensile manipulation: Transfer from simulation to physical system
Reinforcement learning has emerged as a promising methodology for training robot controllers.
Model-based Reinforcement Learning
reinforcement-learning
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