Publications


Apprenticeship Learning and Reinforcement Learning with Application to Robotic Control,
Pieter Abbeel
Ph.D. Dissertation, Stanford University, Computer Science, August 2008
pdf



[ALL | Deep RL | Learning-to-Learn | Apprentice | Sim2Real | Unsupervised | Optimization-based Planning | Belief Space Planning | Hierarchical Planning | Perception | Deformable Objects | Medical Robotics | Helicopter | Connectomics ]


Pre-prints

Transfer from Simulation to Real World through Learning Deep Inverse Dynamics Model,
Paul Christiano, Zain Shah, Igor Mordatch, Jonas Schneider, Trevor Blackwell, Joshua Tobin, Pieter Abbeel, Wojciech Zaremba.
arXiv 1610.03518


Publications

[210] Domain Randomization for Active Pose Estimation,
Xinyi Ren, Jianlan Luo, Eugen Solowjow, Juan Aparicio Ojea, Abhishek Gupta, Aviv Tamar, Pieter Abbeel
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, May 2019.
arXiv 1903.03953

[195] Model-Based Reinforcement Learning via Meta-Policy Optimization,
Ignasi Clavera*, Jonas Rothfuss*, John Schulman, Yasuhiro Fujita, Tamim Asfour, Pieter Abbeel.
In the proceedings of the Conference on Robot Learning (CoRL), Zurich, Switzerland, October 2018.
arXiv 1809.05214

[192] Domain Randomization and Generative Models for Robotic Grasping,
Joshua Tobin, Lukas Biewald, Rocky Duan, Marcin Andrychowicz, Ankur Handa, Vikash Kumar, Bob McGrew, Jonas Schneider, Peter Welinder, Wojciech Zaremba, Pieter Abbeel.
In the proceedings of the IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS), Madrid, Spain, October 2018.
arXiv 1710.06425

[183] Asymmetric Actor Critic for Image-Based Robot Learning,
Lerrel Pinto, Marcin Andrychowicz, Peter Welinder, Wojciech Zaremba, Pieter Abbeel.
In the proceedings of Robotics: Science and Systems (RSS), Pittsburgh, PA, USA, June 2018.
arXiv 1710.06542, videos

[173] Learning Robotic Assembly from CAD, Best Paper Finalist,
Garrett Thomas*, Melissa Chien*, Aviv Tamar, Juan Aparicio Ojea, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, May 2018. (arXiv 1803.07635, video)

[172] Sim-to-Real Transfer of Robotic Control with Dynamics Randomization,
Xue Bin (Jason) Peng, Marcin Andrychowicz, Wojciech Zaremba, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, May 2018. (arXiv 1710.064537, video)

[159] Mutual Alignment Transfer Learning,
Markus Wulfmeier, Ingmar Posner, Pieter Abbeel.
In the proceedings of the 1st Annual Conference on Robot Learning (CoRL), Mountain View, CA, November 2017. (arXiv 1707.07907)

[157] Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World
Josh Tobin, Rachel Fong, Alex Ray, Jonas Schneider, Wojciech Zaremba, Pieter Abbeel.
In the proceedings of the 30th IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS), Vancouver, Canada, October 2017. (arXiv 1703.06907)

[156] Policy Transfer via Modularity
Ignasi Clavera, David Held, Pieter Abbeel.
In the proceedings of the 30th IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS), Vancouver, Canada, October 2017. (pdf)

[135] Towards Adapting Deep Visuomotor Representations from Simulated to Real Environments,
Eric Tzeng, Coline Devin, Judy Hoffman, Chelsea Finn, Pieter Abbeel, Sergey Levine, Kate Saenko, Trevor Darrell.
In the proceedings of the Workshop on Algorithmic Foundations of Robotics (WAFR), San Francisco, CA, USA, December 2016. (arXiv 1511.07111)