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.
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Related Papers
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2025 March |
Whole-Body Model-Predictive Control of Legged Robots with MuJoCo
arxiv (In Review) |
People
John Zhang
Optimization, Control, and Robotics
Taylor Howell
Ph.D. in MechE, Stanford. Now at Google DeepMind.
Zac Manchester
Associate Professor