Geometry-aware Bayesian Optimization in Robotics using Riemannian Matérn Kernels

Noémie Jaquier, Viacheslav Borovitskiy, Andrei Smolensky, Alexander Terenin, Tamim Asfour, Leonel Dario Rozo

Abstract: Bayesian optimization is a data-efficient technique which can be used for control parameter tuning, parametric policy adaptation, and structure design in robotics. Many of these problems require op...