Frederik Heetmeyer

RPGD: A Small-Batch Parallel Gradient Descent Optimizer with Explorative Resampling for Nonlinear Model Predictive Control

Nonlinear model predictive control often involves nonconvex optimization for which real-time control systems require fast and numerically stable solutions. This work proposes RPGD, a Resampling Parallel Gradient Descent optimizer designed to exploit small-batch parallelism of modern hardware like ne…