Se3-nets: Learning rigid body motion using deep neural networks A Byravan, D Fox 2017 IEEE International Conference on Robotics and Automation (ICRA), 173-180, 2017 | 331 | 2017 |
Learning agile soccer skills for a bipedal robot with deep reinforcement learning T Haarnoja, B Moran, G Lever, SH Huang, D Tirumala, J Humplik, ... Science Robotics 9 (89), eadi8022, 2024 | 125 | 2024 |
Beyond pick-and-place: Tackling robotic stacking of diverse shapes AX Lee, CM Devin, Y Zhou, T Lampe, K Bousmalis, JT Springenberg, ... 5th Annual Conference on Robot Learning, 2021 | 108 | 2021 |
Se3-pose-nets: Structured deep dynamics models for visuomotor control A Byravan, F Leeb, F Meier, D Fox 2018 IEEE International Conference on Robotics and Automation (ICRA), 3339-3346, 2018 | 63 | 2018 |
Towards a unified agent with foundation models N Di Palo, A Byravan, L Hasenclever, M Wulfmeier, N Heess, ... arXiv preprint arXiv:2307.09668, 2023 | 56 | 2023 |
Prospection: Interpretable plans from language by predicting the future C Paxton, Y Bisk, J Thomason, A Byravan, D Foxl 2019 International Conference on Robotics and Automation (ICRA), 6942-6948, 2019 | 54 | 2019 |
Learning predictive models of a depth camera & manipulator from raw execution traces B Boots, A Byravan, D Fox 2014 IEEE International Conference on Robotics and Automation (ICRA), 4021-4028, 2014 | 54 | 2014 |
Nerf2real: Sim2real transfer of vision-guided bipedal motion skills using neural radiance fields A Byravan, J Humplik, L Hasenclever, A Brussee, F Nori, T Haarnoja, ... 2023 IEEE International Conference on Robotics and Automation (ICRA), 9362-9369, 2023 | 52 | 2023 |
Space-time functional gradient optimization for motion planning A Byravan, B Boots, SS Srinivasa, D Fox 2014 IEEE International Conference on Robotics and Automation (ICRA), 6499-6506, 2014 | 51 | 2014 |
Imagined value gradients: Model-based policy optimization with tranferable latent dynamics models A Byravan, JT Springenberg, A Abdolmaleki, R Hafner, M Neunert, ... Conference on Robot Learning, 566-589, 2020 | 49 | 2020 |
The challenges of exploration for offline reinforcement learning N Lambert, M Wulfmeier, W Whitney, A Byravan, M Bloesch, V Dasagi, ... arXiv preprint arXiv:2201.11861, 2022 | 41 | 2022 |
Se3-pose-nets: Structured deep dynamics models for visuomotor planning and control A Byravan, F Leeb, F Meier, D Fox arXiv preprint arXiv:1710.00489, 2017 | 39 | 2017 |
Graph-Based Inverse Optimal Control for Robot Manipulation. A Byravan, M Monfort, BD Ziebart, B Boots, D Fox Ijcai 15, 1874-1890, 2015 | 34 | 2015 |
A generalist dynamics model for control I Schubert, J Zhang, J Bruce, S Bechtle, E Parisotto, M Riedmiller, ... arXiv preprint arXiv:2305.10912, 2023 | 28 | 2023 |
Learning dynamics models for model predictive agents M Lutter, L Hasenclever, A Byravan, G Dulac-Arnold, P Trochim, N Heess, ... arXiv preprint arXiv:2109.14311, 2021 | 25 | 2021 |
Towards real robot learning in the wild: A case study in bipedal locomotion M Bloesch, J Humplik, V Patraucean, R Hafner, T Haarnoja, A Byravan, ... Conference on Robot Learning, 1502-1511, 2022 | 24 | 2022 |
On multi-objective policy optimization as a tool for reinforcement learning A Abdolmaleki, SH Huang, G Vezzani, B Shahriari, JT Springenberg, ... arXiv preprint arXiv:2106.08199, 2021 | 20 | 2021 |
Local search for policy iteration in continuous control JT Springenberg, N Heess, D Mankowitz, J Merel, A Byravan, ... arXiv preprint arXiv:2010.05545, 2020 | 18 | 2020 |
Representation matters: Improving perception and exploration for robotics M Wulfmeier, A Byravan, T Hertweck, I Higgins, A Gupta, T Kulkarni, ... 2021 IEEE International Conference on Robotics and Automation (ICRA), 6512-6519, 2021 | 17 | 2021 |
Evaluating model-based planning and planner amortization for continuous control A Byravan, L Hasenclever, P Trochim, M Mirza, AD Ialongo, Y Tassa, ... arXiv preprint arXiv:2110.03363, 2021 | 15 | 2021 |