Article

Analysis of Sampling and Derivative Predictive Control for Real-Time Behavior Synthesis in MuJoCo MPC

Gu Yue Ju analyzes the MuJoCo real-time predictive control framework, which uses a residual cost to unify task descriptions, with four planners—predictive sampling, gradient descent, iLQG, and hybrid ILQS—replanning at every step within the same loop. A Cartpole comparison experiment reports the convergence speed and per-step computational cost of the four.

Part of the event: Comparative Analysis of Four Planners in the Same Loop for MuJoCo MPC

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