mlsanityData to 14 Oct 2026

The Duke Humanoid: Design and Control For Energy Efficient Bipedal Locomotion Using Passive Dynamics

arXiv 2409.19795 ↗First posted 29 Sep 2024cs.ROcited by 2

On the map: Deep reinforcement learning methods → RL for robot locomotion and manipulation

Abstract (arXiv)

We present the Duke Humanoid, an open-source 10-degrees-of-freedom humanoid, as an extensible platform for locomotion research. The design mimics human physiology, with symmetrical body alignment in the frontal plane to maintain static balance with straight knees. We develop a reinforcement learning policy that can be deployed zero-shot on the hardware for velocity-tracking walking tasks. Additionally, to enhance energy efficiency in locomotion, we propose an end-to-end reinforcement learning algorithm that encourages the robot to leverage passive dynamics. Our experimental results show that our passive policy reduces the cost of transport by up to 50% in simulation and 31% in real-world tests. Our website is http://generalroboticslab.com/DukeHumanoidv1/ .

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in RL for robot locomotion and manipulation, one of 15 directions in Deep reinforcement learning methods. Builds on 16 of its 48 references that are in the map. First posted on arXiv 29 Sep 2024.

Builds on

16 of 48 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024Advancing Humanoid Locomotion: Mastering Challenging Terrains with Denoising World Model Learning26 Aug

Other references · 15

  1. 2015Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)cited by 1,070
  2. 2021Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learningcited by 998
  3. 2020Learning Quadrupedal Locomotion over Challenging Terraincited by 604
  4. 2021Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learningcited by 512
  5. 2019Learning agile and dynamic motor skills for legged robotscited by 504
  6. 2019Learning by Cheatingcited by 383
  7. 2022Learning robust perceptive locomotion for quadrupedal robots in the wildcited by 382
  8. 2023Real-World Humanoid Locomotion with Reinforcement Learningcited by 187
  9. 2018DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skillscited by 163
  10. 2021Fast and Efficient Locomotion via Learned Gait Transitionscited by 54
  11. 2023Deep Imitation Learning for Humanoid Loco-manipulation through Human Teleoperationcited by 54
  12. 2024Berkeley Humanoid: A Research Platform for Learning-based Controlcited by 24
3 more
  1. 2019MPC for Humanoid Gait Generation: Stability and Feasibilitycited by 6
  2. 2023Dynamic Loco-manipulation on HECTOR: Humanoid for Enhanced ConTrol and Open-source Researchcited by 5
  3. 2018NimbRo-OP2X: Adult-sized Open-source 3D Printed Humanoid Robotcited by 2

Built on by

Cited by year

Citing papers per year: 2025: 2.

2 papers.

  1. 2025Embrace Collisions: Humanoid Shadowing for Deployable Contact-Agnostics Motionscited by 7
  2. 2025LAPP: Large Language Model Feedback for Preference-Driven Reinforcement Learningcited by 2

Similar, not cited

Close in wording, no citation either way

  1. 2026Model-Based Reinforcement Learning Exploits Passive Body Dynamics for High-Performance Biped Robot Locomotion
  2. 2026Passive-Dynamic-Walking-Inspired Dynamics Guidance for Energy-Efficient Humanoid Locomotion ↗
  3. 2025Reduced-Order Model-Guided Reinforcement Learning for Demonstration-Free Humanoid Locomotion
  4. 2025Humanoid Locomotion and Manipulation: Current Progress and Challenges in Control, Planning, and Learning
  5. 2024Deep Reinforcement Learning for Bipedal Locomotion: A Brief Survey
  6. 2024Agile and versatile bipedal robot tracking control through reinforcement learning
  7. 2026ECO: Energy-Constrained Optimization with Reinforcement Learning for Humanoid Walking
  8. 2025RuN: Residual Policy for Natural Humanoid Locomotion