References

Papers and projects related to the course project.

More references will be added during the semester.

Review: humanoid locomotion control

Humanoid locomotion control review: paper
Gu et al., “Evolution of humanoid locomotion control”, Science Robotics, 2026

Berkeley Humanoid: paper · project website
Liao et al., “Berkeley Humanoid: A Research Platform for Learning-based Control”, 2024 (arXiv:2407.21781)
Berkeley Humanoid Lite: paper · project website · documentation
Chi et al., “Demonstrating Berkeley Humanoid Lite: An Open-source, Accessible, and Customizable 3D-printed Humanoid Robot”, 2025 (arXiv:2504.17249)
MEVITA: paper · project website
Kawaharazuka et al., “MEVITA: Open-Source Bipedal Robot Assembled from E-Commerce Components via Sheet Metal Welding”, 2025 (arXiv:2508.17684)
Duke Humanoid: paper · project website
Xia et al., “The Duke Humanoid: Design and Control For Energy Efficient Bipedal Locomotion Using Passive Dynamics”, 2024 (arXiv:2409.19795)
MIT Humanoid: paper
Chignoli et al., “The MIT Humanoid Robot: Design, Motion Planning, and Control For Acrobatic Behaviors”, 2021 (arXiv:2104.09025)
ROBOTIS OH! GYM!: project website
ROBOTIS, “OH! GYM! (Open Humanoid GYM)”: an open humanoid platform and development environment
ROBOTIS open source: documentation
ROBOTIS’s open-source projects, including humanoid robots, simulation models, and hardware documentation

Bipedal robotic character: paper
Grandia et al., “Design and Control of a Bipedal Robotic Character”, 2025 (arXiv:2501.05204)
Olaf: paper
Müller et al., “Olaf: Bringing an Animated Character to Life in the Physical World”, 2025 (arXiv:2512.16705)
Walk Like This: project website
Aurand et al., “Walk Like This: Stylized Locomotion for Physics-Based Characters through Example-Driven Diffusion”, Conference on Robot Learning (CoRL), 2026
Kamino: paper · project website
Tsounis et al., “Kamino: GPU-based Massively Parallel Simulation of Multi-Body Systems with Challenging Topologies”, 2026 (arXiv:2603.16536)

awesome-humanoid-robot-learning: GitHub
A curated list of research papers on humanoid robot learning. We recommend it for finding papers on the topic.