Aleksei Petrenko

According to our database, Aleksei Petrenko authored at least 10 papers between 2020 and 2023.

Collaborative distances:

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

2023

QuadSwarm: A Modular Multi-Quadrotor Simulator for Deep Reinforcement Learning with Direct Thrust Control.

Zhehui Huang, Sumeet Batra, Tao Chen, Rahul Krupani, Tushar Kumar, Artem Molchanov, Aleksei Petrenko, James A. Preiss, Zhaojing Yang, Gaurav S. Sukhatme

CoRR, 2023

Proximal Policy Gradient Arborescence for Quality Diversity Reinforcement Learning.

Sumeet Batra, Bryon Tjanaka, Matthew C. Fontaine, Aleksei Petrenko, Stefanos Nikolaidis, Gaurav S. Sukhatme

CoRR, 2023

DexPBT: Scaling up Dexterous Manipulation for Hand-Arm Systems with Population Based Training.

Aleksei Petrenko, Arthur Allshire, Gavriel State, Ankur Handa, Viktor Makoviychuk

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

DeXtreme: Transfer of Agile In-hand Manipulation from Simulation to Reality.

Ankur Handa, Arthur Allshire, Viktor Makoviychuk, Aleksei Petrenko, Ritvik Singh, Jingzhou Liu, Denys Makoviichuk, Karl Van Wyk, Alexander Zhurkevich, Balakumar Sundaralingam, Yashraj S. Narang

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

2022

DeXtreme: Transfer of Agile In-hand Manipulation from Simulation to Reality.

Ankur Handa, Arthur Allshire, Viktor Makoviychuk, Aleksei Petrenko, Ritvik Singh, Jingzhou Liu, Denys Makoviichuk, Karl Van Wyk, Alexander Zhurkevich, Balakumar Sundaralingam, Yashraj S. Narang, Jean-Francois Lafleche, Dieter Fox, Gavriel State

CoRR, 2022

2021

Megaverse: Simulating Embodied Agents at One Million Experiences per Second.

Aleksei Petrenko, Erik Wijmans, Brennan Shacklett, Vladlen Koltun

Proceedings of the 38th International Conference on Machine Learning, 2021

Large Batch Simulation for Deep Reinforcement Learning.

Brennan Shacklett, Erik Wijmans, Aleksei Petrenko, Manolis Savva, Dhruv Batra, Vladlen Koltun, Kayvon Fatahalian

Proceedings of the 9th International Conference on Learning Representations, 2021

Decentralized Control of Quadrotor Swarms with End-to-end Deep Reinforcement Learning.

Sumeet Batra, Zhehui Huang, Aleksei Petrenko, Tushar Kumar, Artem Molchanov, Gaurav S. Sukhatme

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

Agents that Listen: High-Throughput Reinforcement Learning with Multiple Sensory Systems.

Shashank Hegde, Anssi Kanervisto, Aleksei Petrenko

Proceedings of the 2021 IEEE Conference on Games (CoG), 2021

2020

Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning.

Aleksei Petrenko, Zhehui Huang, Tushar Kumar, Gaurav S. Sukhatme, Vladlen Koltun

Proceedings of the 37th International Conference on Machine Learning, 2020