Sample factory: Egocentric 3d control from pixels at 100000 fps with asynchronous reinforcement learning A Petrenko, Z Huang, T Kumar, G Sukhatme, V Koltun International Conference on Machine Learning, 7652-7662, 2020 | 71 | 2020 |
Dextreme: Transfer of agile in-hand manipulation from simulation to reality A Handa, A Allshire, V Makoviychuk, A Petrenko, R Singh, J Liu, ... 2023 IEEE International Conference on Robotics and Automation (ICRA), 5977-5984, 2023 | 68* | 2023 |
Decentralized control of quadrotor swarms with end-to-end deep reinforcement learning S Batra, Z Huang, A Petrenko, T Kumar, A Molchanov, GS Sukhatme Conference on Robot Learning, 576-586, 2022 | 37 | 2022 |
Large batch simulation for deep reinforcement learning B Shacklett, E Wijmans, A Petrenko, M Savva, D Batra, V Koltun, ... International Conference on Learning Representations, 2021, 2021 | 23 | 2021 |
Megaverse: Simulating embodied agents at one million experiences per second A Petrenko, E Wijmans, B Shacklett, V Koltun International Conference on Machine Learning, 8556-8566, 2021 | 18 | 2021 |
Dexpbt: Scaling up dexterous manipulation for hand-arm systems with population based training A Petrenko, A Allshire, G State, A Handa, V Makoviychuk arXiv preprint arXiv:2305.12127, 2023 | 9 | 2023 |
Agents that listen: High-throughput reinforcement learning with multiple sensory systems S Hegde, A Kanervisto, A Petrenko 2021 IEEE Conference on Games (CoG), 1-5, 2021 | 8 | 2021 |
Proximal policy gradient arborescence for quality diversity reinforcement learning S Batra, B Tjanaka, MC Fontaine, A Petrenko, S Nikolaidis, G Sukhatme arXiv preprint arXiv:2305.13795, 2023 | 5 | 2023 |
Quadswarm: A modular multi-quadrotor simulator for deep reinforcement learning with direct thrust control Z Huang, S Batra, T Chen, R Krupani, T Kumar, A Molchanov, A Petrenko, ... arXiv preprint arXiv:2306.09537, 2023 | 4 | 2023 |
Ai-based control for robotics systems and applications A Handa, AD Allshire, V Makoviichuk, AV Petrenko US Patent App. 18/330,905, 2024 | | 2024 |
Training machine learning models using simulation for robotics systems and applications A Handa, AD Allshire, D Fox, JFV Lafleche, LIU Jingzhou, V Makoviichuk, ... US Patent App. 18/448,049, 2024 | | 2024 |