Efficient Quadruped Mobility: Harnessing a Generalist Policy for Streamlined Planning

GHC 4405

Abstract: Navigating quadruped robots through complex, unstructured environments over long horizons remains a significant challenge in robotics. Traditional planning methods offer guarantees such as optimality and long-horizon reasoning, while learning-based methods, particularly those involving deep reinforcement learning (DRL), provide robustness and generalization. In this thesis, we present S3D-OWNS (Skilled 3D-Optimal Waypoint Navigation System), a novel [...]