Our paper, Exciting Action: Investigating Efficient Exploration for Learning Musculoskeletal Humanoid Locomotion, was accepted at the International Conference on Humanoid Robots. In this work, we address the challenges of learning a locomotion controller for musculoskeletal systems, particularly the issues of over-actuation and high-dimensional action spaces. While reinforcement learning methods have struggled to generate human-like gaits […]
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