5 papers
Dojo: A Differentiable Physics Engine for Robotics
Taylor A. Howell, Simon Le Cleac'h, Jan Brüdigam +5
We present Dojo, a differentiable physics engine for robotics that prioritizes stable simulation, accurate contact physics, and differentiability with respect to states, actions, a…
Reachable Polyhedral Marching (RPM): An Exact Analysis Tool for Deep-Learned Control Systems
Joseph A. Vincent, Mac Schwager
Neural networks are increasingly used in robotics as policies, state transition models, state estimation models, or all of the above. With these components being learned from data,…
Distributed Optimization Methods for Multi-Robot Systems: Part II -- A Survey
Ola Shorinwa, Trevor Halsted, Javier Yu +1
Although the field of distributed optimization is well-developed, relevant literature focused on the application of distributed optimization to multi-robot problems is limited. Thi…
Distributed Optimization Methods for Multi-Robot Systems: Part I -- A Tutorial
Ola Shorinwa, Trevor Halsted, Javier Yu +1
Distributed optimization provides a framework for deriving distributed algorithms for a variety of multi-robot problems. This tutorial constitutes the first part of a two-part seri…
OA-MPC: Occlusion-Aware MPC for Guaranteed Safe Robot Navigation with Unseen Dynamic Obstacles
Roya Firoozi, Alexandre Mir, Gadi Sznaier Camps +1
For safe navigation in dynamic uncertain environments, robotic systems rely on the perception and prediction of other agents. Particularly, in occluded areas where cameras and LiDA…