1 code implementation • 11 Nov 2021 • I-Chun Arthur Liu, Shagun Uppal, Gaurav S. Sukhatme, Joseph J. Lim, Peter Englert, Youngwoon Lee
Learning complex manipulation tasks in realistic, obstructed environments is a challenging problem due to hard exploration in the presence of obstacles and high-dimensional visual observations.
1 code implementation • 24 Oct 2020 • Benedek Rozemberczki, Peter Englert, Amol Kapoor, Martin Blais, Bryan Perozzi
Additional results from a challenging suite of node classification experiments show how PDNs can learn a wider class of functions than existing baselines.
no code implementations • 22 Oct 2020 • Jun Yamada, Youngwoon Lee, Gautam Salhotra, Karl Pertsch, Max Pflueger, Gaurav S. Sukhatme, Joseph J. Lim, Peter Englert
In contrast, motion planners use explicit models of the agent and environment to plan collision-free paths to faraway goals, but suffer from inaccurate models in tasks that require contacts with the environment.
1 code implementation • 24 Sep 2020 • Giovanni Sutanto, Isabel M. Rayas Fernández, Peter Englert, Ragesh K. Ramachandran, Gaurav S. Sukhatme
Constrained robot motion planning is a widely used technique to solve complex robot tasks.
1 code implementation • 13 Jun 2020 • Isabel M. Rayas Fernández, Giovanni Sutanto, Peter Englert, Ragesh K. Ramachandran, Gaurav S. Sukhatme
Motion planning with constraints is an important part of many real-world robotic systems.
Robotics Computational Geometry
1 code implementation • 3 Jun 2020 • Peter Englert, Isabel M. Rayas Fernández, Ragesh K. Ramachandran, Gaurav S. Sukhatme
We address the problem of planning robot motions in constrained configuration spaces where the constraints change throughout the motion.
Robotics Computational Geometry
no code implementations • 5 Mar 2018 • Peter Englert, Marc Toussaint
The transfer of a robot skill between different geometric environments is non-trivial since a wide variety of environments exists, sensor observations as well as robot motions are high-dimensional, and the environment might only be partially observed.
no code implementations • 23 Jan 2017 • Andrea Baisero, Stefan Otte, Peter Englert, Marc Toussaint
Successful human-robot cooperation hinges on each agent's ability to process and exchange information about the shared environment and the task at hand.
no code implementations • 2 Jul 2013 • Marc Peter Deisenroth, Peter Englert, Jan Peters, Dieter Fox
Learning policies that generalize across multiple tasks is an important and challenging research topic in reinforcement learning and robotics.