Real-Time Whole-Body MPC for Legged Robots with MuJoCo
We show that simple model-predictive controls algorithms such as iLQR can be surprisingly effective at enabling a variety of whole-body control behaviors on high dimensional legged robtots (i.e. quadrupeds and humanoids) in the real world.
Checkout our website.
Related Papers
|
2026 June |
Whole-Body Model-Predictive Control of Legged Robots with MuJoCo
IEEE International Conference on Robotics and Automation (ICRA). Vienna, Austria. (Accepted) |
People
John Zhang
Optimization, Control, and Robotics
Taylor Howell
Ph.D. in MechE, Stanford. Now at Google DeepMind.
Zac Manchester
Associate Professor