Direct Policy Optimization Paper Accepted to RAL

April 04, 2021

Taylor’s “Direct Policy Optimization using Deterministic Sampling and Collocation” paper was accepted to Robotics and Automation Letters (RA-L) and will be presented at ICRA 2021. The paper presents an approach that combines direct trajectory optimization, the unscented transform, and policy optimization in order to synthesize feedback policies.