OTHER
SBMPO: Sampling Based Model Predictive Optimization for robot trajectory planning
Mario Harper, Camilo Ordóñez, Emmanuel G. Collins
- Year
- 2021
- Citations
- 3
Abstract
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.
Keywords
Model predictive controlComputer scienceTrajectoryRoboticsMotion planningTrajectory optimizationArtificial intelligenceNonlinear modelTask (project management)Scheduling (production processes)
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