SBMPO: Sampling Based Model Predictive Optimization for robot trajectory planning

Sampling-Based Model Predictive Control (SBMPO) is a novel nonlinear MPC (NMPC) approach that enables motion planning with dynamic models. This tool is also well suited to solve traditional MPC problems and has been tested in various situations ranging from robotics, task scheduling, resource management, combustion processes, and general optimization.

Automated summary

Sampling-Based Model Predictive Control (SBMPO) is a novel approach to nonlinear MPC that enables motion planning with dynamic models. It is suitable for solving traditional MPC problems and has been tested in various scenarios such as robotics, task scheduling, resource management, combustion processes, and general optimization.