mlsanityData to 7 Oct 2026

Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation

arXiv 2412.03949 ↗First posted 5 Dec 2024cs.RO cs.LGcited by 4

On the map: Offline RL and imitation learning from data → Real-world robot offline RL

Abstract (arXiv)

Virtual models of human gait, or digital twins, offer a promising solution for studying mobility without the need for labor-intensive data collection. However, challenges such as the sim-to-real gap and limited adaptability to diverse walking conditions persist. To address these, we developed and validated a framework to create a skeletal humanoid agent capable of adapting to varying walking speeds while maintaining biomechanically realistic motions. The framework combines a synthetic data generator, which produces biomechanically plausible gait kinematics from open-source biomechanics data, and a training system that uses adversarial imitation learning to train the agent's walking policy. We conducted comprehensive analyses comparing the agent's kinematics, synthetic data, and the original biomechanics dataset. The agent achieved a root mean square error of 5.24 +- 0.09 degrees at varying speeds compared to ground-truth kinematics data, demonstrating its adaptability. This work represents a significant step toward developing a digital twin of human locomotion, with potential applications in biomechanics research, exoskeleton design, and rehabilitation.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Placed in Real-world robot offline RL, one of 13 directions in Offline RL and imitation learning from data. Builds on 9 of its 38 references that are in the map. First posted on arXiv 5 Dec 2024.

Builds on

9 of 38 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023LocoMuJoCo: A Comprehensive Imitation Learning Benchmark for Locomotion4 Nov

Other references · 8

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,635
  3. 2015Trust Region Policy Optimizationcited by 2,503
  4. 2015Unsupervised Deep Embedding for Clustering Analysiscited by 763
  5. 2018DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skillscited by 153
  6. 2018Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flowcited by 103
  7. 2019Learning a Control Policy for Fall Prevention on an Assistive Walking Devicecited by 4
  8. 2023Natural and Robust Walking using Reinforcement Learning without Demonstrations in High-Dimensional Musculoskeletal Modelscited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 3.

4 papers.

  1. 2026Learning Hip Exoskeleton Control Policy via Predictive Neuromusculoskeletal Simulationcited by 1
  2. 2026Muscle Synergy Priors Enhance Biomechanical Fidelity in Predictive Musculoskeletal Locomotion Simulationcited by 1
  3. 2025Coupled Distributional Random Expert Distillation for World Model Online Imitation Learningcited by 0
  4. 2026Imitation Learning from Human Motion Alone Does Not Guarantee Biomechanically Plausible Gait Kineticscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Exciting Action: Investigating Efficient Exploration for Learning Musculoskeletal Humanoid Locomotion
  2. 2026Biomechanical Comparisons Reveal Divergence of Human and Humanoid Gaits ↗
  3. 2023HumanMimic: Learning Natural Locomotion and Transitions for Humanoid Robot via Wasserstein Adversarial Imitation
  4. 2025Think on your feet: Seamless Transition between Human-like Locomotion in Response to Changing Commands
  5. 2025KinTwin: Imitation Learning with Torque and Muscle Driven Biomechanical Models Enables Precise Replication of Able-Bodied and Impaired Movement from Markerless Motion Capture
  6. 2019Self-Imitation Learning of Locomotion Movements through Termination Curriculum
  7. 2025StyleLoco: Generative Adversarial Distillation for Natural Humanoid Robot Locomotion
  8. 2021Adaptive Mimic: Deep Reinforcement Learning of Parameterized Bipedal Walking from Infeasible References ↗