Research#
Citing mjlab#
If you use mjlab in your research, please cite:
@article{Zakka_mjlab_A_Lightweight_2026,
author = {Zakka, Kevin and Liao, Qiayuan and Yi, Brent and Le Lay, Louis and Sreenath, Koushil and Abbeel, Pieter},
title = {{mjlab: A Lightweight Framework for GPU-Accelerated Robot Learning}},
url = {https://arxiv.org/abs/2601.22074},
year = {2026}
}
Publications#
Papers that use mjlab. To add your work, open a pull request or post in Show and Tell.
Title |
Authors |
Year |
|---|---|---|
HUSKY: Humanoid Skateboarding System via Physics-Aware Whole-Body Control |
Han, Wang, Zhang, Liu, Luo, Bai, Li |
2026 |
DynaRetarget: Dynamically-Feasible Retargeting using Sampling-Based Trajectory Optimization |
Dhedin, Taouil, Omar, Yu, Tao, Dai, Khadiv |
2026 |
Projects#
Projects built on mjlab. To add yours, open a pull request or post in Show and Tell.
Project |
Description |
|---|---|
Locomotion fork for the Asimov bipedal robot. |
|
H1 locomotion across multiple tasks with robustness to upper body disturbances. |
|
Musculoskeletal simulation integration with MyoSuite. |
|
Velocity control for the Upkie wheeled biped. |
|
Official Unitree RL environments for Go2, G1, and H1_2. |
|
Sim to real RL for in hand cube rotation with the LEAP Hand. |