CMU Research Introduces CoVO-MPC (Covariance-Optimal MPC): A Novel Sampling-based MPC Algorithm that Optimizes the Convergence Rate

Model Predictive Control (MPC) has become a key technology in a number of fields, including power systems, robotics, transportation, and process control. Sampling-based MPC has shown effectiveness in applications such as path planning and control, and it is useful as a subroutine in Model-Based Reinforcement Learning (MBRL), all because of its versatility and parallelizability,  Despite […]

The post CMU Research Introduces CoVO-MPC (Covariance-Optimal MPC): A Novel Sampling-based MPC Algorithm that Optimizes the Convergence Rate appeared first on MarkTechPost.

ai shorts algorithm applications artificial intelligence become cmu control convergence covariance editors pick fields key machine learning mpc novel path planning power predictive process rate research robotics sampling staff systems tech news technology transportation