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Found 3 papers, 1 papers with code
Learning Low-Frequency Motion Control for Robust and Dynamic Robot Locomotion
Robotic locomotion is often approached with the goal of maximizing robustness and reactivity by increasing motion control frequency.
Learning and Deploying Robust Locomotion Policies with Minimal Dynamics Randomization
This allows us to obtain locomotion policies that are robust to variations in system dynamics.
CPG-ACTOR: Reinforcement Learning for Central Pattern Generators
Our results on a locomotion task using a single-leg hopper demonstrate that explicitly using the CPG as the Actor rather than as part of the environment results in a significant increase in the reward gained over time (6x more) compared with previous approaches.
Robotics
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