Arunkumar Byravan

According to our database, Arunkumar Byravan authored at least 30 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Learning agile soccer skills for a bipedal robot with deep reinforcement learning.

Tuomas Haarnoja, Ben Moran, Guy Lever, Sandy H. Huang, Dhruva Tirumala, Jan Humplik, Markus Wulfmeier, Saran Tunyasuvunakool, Noah Y. Siegel, Roland Hafner, Michael Bloesch, Kristian Hartikainen, Arunkumar Byravan, Leonard Hasenclever, Yuval Tassa, Fereshteh Sadeghi, Nathan Batchelor, Federico Casarini, Stefano Saliceti, Charles Game, Neil Sreendra, Kushal Patel, Marlon Gwira, Andrea Huber, Nicole Hurley, Francesco Nori, Raia Hadsell, Nicolas Heess

Sci. Robotics, 2024

Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning.

Dhruva Tirumala, Markus Wulfmeier, Ben Moran, Sandy H. Huang, Jan Humplik, Guy Lever, Tuomas Haarnoja, Leonard Hasenclever, Arunkumar Byravan, Nathan Batchelor, Neil Sreendra, Kushal Patel, Marlon Gwira, Francesco Nori, Martin A. Riedmiller, Nicolas Heess

CoRR, 2024

Real-World Fluid Directed Rigid Body Control via Deep Reinforcement Learning.

Mohak Bhardwaj, Thomas Lampe, Michael Neunert, Francesco Romano, Abbas Abdolmaleki, Arunkumar Byravan, Markus Wulfmeier, Martin A. Riedmiller, Jonas Buchli

CoRR, 2024

2023

Foundations for Transfer in Reinforcement Learning: A Taxonomy of Knowledge Modalities.

Markus Wulfmeier, Arunkumar Byravan, Sarah Bechtle, Karol Hausman, Nicolas Heess

CoRR, 2023

Equivariant Data Augmentation for Generalization in Offline Reinforcement Learning.

Cristina Pinneri, Sarah Bechtle, Markus Wulfmeier, Arunkumar Byravan, Jingwei Zhang, William F. Whitney, Martin A. Riedmiller

CoRR, 2023

Towards A Unified Agent with Foundation Models.

Norman Di Palo, Arunkumar Byravan, Leonard Hasenclever, Markus Wulfmeier, Nicolas Heess, Martin A. Riedmiller

CoRR, 2023

A Generalist Dynamics Model for Control.

Ingmar Schubert, Jingwei Zhang, Jake Bruce, Sarah Bechtle, Emilio Parisotto, Martin A. Riedmiller, Jost Tobias Springenberg, Arunkumar Byravan, Leonard Hasenclever, Nicolas Heess

CoRR, 2023

Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains.

Jingwei Zhang, Jost Tobias Springenberg, Arunkumar Byravan, Leonard Hasenclever, Abbas Abdolmaleki, Dushyant Rao, Nicolas Heess, Martin A. Riedmiller

CoRR, 2023

NeRF2Real: Sim2real Transfer of Vision-guided Bipedal Motion Skills using Neural Radiance Fields.

Arunkumar Byravan, Jan Humplik, Leonard Hasenclever, Arthur Brussee, Francesco Nori, Tuomas Haarnoja, Ben Moran, Steven Bohez, Fereshteh Sadeghi, Bojan Vujatovic, Nicolas Heess

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022

Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach.

Bobak Shahriari, Abbas Abdolmaleki, Arunkumar Byravan, Abe Friesen, Siqi Liu, Jost Tobias Springenberg, Nicolas Heess, Matt Hoffman, Martin A. Riedmiller

CoRR, 2022

The Challenges of Exploration for Offline Reinforcement Learning.

Nathan Lambert, Markus Wulfmeier, William F. Whitney, Arunkumar Byravan, Michael Bloesch, Vibhavari Dasagi, Tim Hertweck, Martin A. Riedmiller

CoRR, 2022

Evaluating Model-Based Planning and Planner Amortization for Continuous Control.

Arunkumar Byravan, Leonard Hasenclever, Piotr Trochim, Mehdi Mirza, Alessandro Davide Ialongo, Yuval Tassa, Jost Tobias Springenberg, Abbas Abdolmaleki, Nicolas Heess, Josh Merel, Martin A. Riedmiller

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Learning Dynamics Models for Model Predictive Agents.

Michael Lutter, Leonard Hasenclever, Arunkumar Byravan, Gabriel Dulac-Arnold, Piotr Trochim, Nicolas Heess, Josh Merel, Yuval Tassa

CoRR, 2021

On Multi-objective Policy Optimization as a Tool for Reinforcement Learning.

Abbas Abdolmaleki, Sandy H. Huang, Giulia Vezzani, Bobak Shahriari, Jost Tobias Springenberg, Shruti Mishra, Dhruva TB, Arunkumar Byravan, Konstantinos Bousmalis, András György, Csaba Szepesvári, Raia Hadsell, Nicolas Heess, Martin A. Riedmiller

CoRR, 2021

Representation Matters: Improving Perception and Exploration for Robotics.

Markus Wulfmeier, Arunkumar Byravan, Tim Hertweck, Irina Higgins, Ankush Gupta, Tejas Kulkarni, Malcolm Reynolds, Denis Teplyashin, Roland Hafner, Thomas Lampe, Martin A. Riedmiller

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes.

Alex X. Lee, Coline Manon Devin, Yuxiang Zhou, Thomas Lampe, Konstantinos Bousmalis, Jost Tobias Springenberg, Arunkumar Byravan, Abbas Abdolmaleki, Nimrod Gileadi, David Khosid, Claudio Fantacci, Jose Enrique Chen, Akhil Raju, Rae Jeong, Michael Neunert, Antoine Laurens, Stefano Saliceti, Federico Casarini, Martin A. Riedmiller, Raia Hadsell, Francesco Nori

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Towards Real Robot Learning in the Wild: A Case Study in Bipedal Locomotion.

Michael Bloesch, Jan Humplik, Viorica Patraucean, Roland Hafner, Tuomas Haarnoja, Arunkumar Byravan, Noah Yamamoto Siegel, Saran Tunyasuvunakool, Federico Casarini, Nathan Batchelor, Francesco Romano, Stefano Saliceti, Martin A. Riedmiller, S. M. Ali Eslami, Nicolas Heess

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

Local Search for Policy Iteration in Continuous Control.

Jost Tobias Springenberg, Nicolas Heess, Daniel J. Mankowitz, Josh Merel, Arunkumar Byravan, Abbas Abdolmaleki, Jackie Kay, Jonas Degrave, Julian Schrittwieser, Yuval Tassa, Jonas Buchli, Dan Belov, Martin A. Riedmiller

CoRR, 2020

2019

Structured Deep Visual Dynamics Models for Robot Manipulation.

Arunkumar Byravan

PhD thesis, 2019

Motion-Nets: 6D Tracking of Unknown Objects in Unseen Environments using RGB.

Felix Leeb, Arunkumar Byravan, Dieter Fox

CoRR, 2019

Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models.

Arunkumar Byravan, Jost Tobias Springenberg, Abbas Abdolmaleki, Roland Hafner, Michael Neunert, Thomas Lampe, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller

CoRR, 2019

Prospection: Interpretable plans from language by predicting the future.

Chris Paxton, Yonatan Bisk, Jesse Thomason, Arunkumar Byravan, Dieter Fox

Proceedings of the International Conference on Robotics and Automation, 2019

Imagined Value Gradients: Model-Based Policy Optimization with Tranferable Latent Dynamics Models.

Arunkumar Byravan, Jost Tobias Springenberg, Abbas Abdolmaleki, Roland Hafner, Michael Neunert, Thomas Lampe, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

2018

SE3-Pose-Nets: Structured Deep Dynamics Models for Visuomotor Control.

Arunkumar Byravan, Felix Leeb, Franziska Meier, Dieter Fox

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

2017

SE3-Pose-Nets: Structured Deep Dynamics Models for Visuomotor Planning and Control.

Arunkumar Byravan, Felix Leeb, Franziska Meier, Dieter Fox

CoRR, 2017

SE3-nets: Learning rigid body motion using deep neural networks.

Arunkumar Byravan, Dieter Fox

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

2016

Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces.

Zita Marinho, Byron Boots, Anca D. Dragan, Arunkumar Byravan, Geoffrey J. Gordon, Siddhartha S. Srinivasa

Proceedings of the Robotics: Science and Systems XII, University of Michigan, Ann Arbor, Michigan, USA, June 18, 2016

2015

Graph-Based Inverse Optimal Control for Robot Manipulation.

Arunkumar Byravan, Mathew Monfort, Brian D. Ziebart, Byron Boots, Dieter Fox

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2014

Space-time functional gradient optimization for motion planning.

Arunkumar Byravan, Byron Boots, Siddhartha S. Srinivasa, Dieter Fox

Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

Learning predictive models of a depth camera & manipulator from raw execution traces.

Byron Boots, Arunkumar Byravan, Dieter Fox

Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014