UC Berkeley Robot Learning Lab: Research

Current Research Directions

A lot of our research is driven by trying to build ever more intelligent systems, which has us pushing the frontiers of deep reinforcement learning, deep imitation learning, deep unsupervised learning, transfer learning, meta-learning, and learning to learn, as well as study the influence of AI on society.

We also like to investigate how AI could open up new opportunities in other disciplines. It's our general belief that if a science or engineering discipline heavily relies on human intuition acquired from seeing many scenarios then it is likely a great fit for AI to help out.

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Publications

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

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Recent Pre-prints

Fleet-DAgger: Interactive Robot Fleet Learning with Scalable Human Supervision,
Ryan Hoque, Lawrence Yunliang Chen, Satvik Sharma, Karthik Dharmarajan, Brijen Thananjeyan, Pieter Abbeel, Ken Goldberg.
tl;dr, arxiv

Masked World Models for Visual Control,
Younggyo Seo, Danijar Hafner, Hao Liu, Fangchen Liu, Stephen James, Kimin Lee, Pieter Abbeel.
tl;dr, arxiv

DayDreamer: World Models for Physical Robot Learning,
Philipp Wu, Alejandro Escontrela, Danijar Hafner, Ken Goldberg, Pieter Abbeel.
tl;dr, arxiv, www, YouTube

Director: Deep Hierarchical Planning from Pixels,
Danijar Hafner, Kuang-Huei Lee, Ian Fischer, Pieter Abbeel.
tl;dr, arxiv, www

Patch-based Object-centric Transformers for Efficient Video Generation,
Wilson Yan, Ryo Okumura, Stephen James, Pieter Abbeel.
tl;dr, code

On the Effectiveness of Fine-tuning Versus Meta-reinforcement Learning,
Zhao Mandi, Pieter Abbeel, Stephen James.
tl;dr, arxiv

Chain of Thought Imitation with Procedure Cloning,
Mengjiao (Sherry) Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum.
tl;dr, arxiv

Toggle Older Preprints

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Publications

[303] Autoregressive Uncertainty Modeling for 3D Bounding Box Prediction,
YuXuan (Andrew) Liu, Nikhil Mishra, Maximilian Sieb, Fred Shentu, Pieter Abbeel, Peter Chen.
In the proceedings of the European Conference on Computer Vision (ECCV), Tel-Aviv, Israel, October 2022
pdf forthcoming

[302] Sim-to-Real 6D Object Pose Estimation via Iterative Self-training for Robotic Bin-picking,
Kai Chen, Rui Cao, Stephen James, Yichuan Li, Yun-Hui Liu, Pieter Abbeel, Qi Dou.
In the proceedings of the European Conference on Computer Vision (ECCV), Tel-Aviv, Israel, October 2022
tl;dr, arXiv 2204.07049

[301] Multi-Objective Policy Gradients with Topological Constraints,
Kyle Wray Stas Tiomkin, Mykel Korchenderfer, Pieter Abbeel.
In the proceedings of the IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS), Kyoto, Japan, October 2022
pdf forthcoming

[300] Learning Visual Robotic Control Efficiently with Contrastive Pre-training and Data Augmentation,
Albert Zhan, Ruihan (Philip) Zhao, Lerrel Pinto, Pieter Abbeel, Misha Laskin.
In the proceedings of the IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS), Kyoto, Japan, October 2022
pdf forthcoming

[299] Adversarial Motion Priors Make Good Substitutes for Complex Reward Functions,
Alejandro Escontrela, Xue Bin Peng, Wenhao Yu, Tingnan Zhang, Atil Iscen, Ken Goldberg, Pieter Abbeel.
In the proceedings of the IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS), Kyoto, Japan, October 2022
arXiv 2203.15103

[298] Playful Interactions for Representation Learning,
Sarah Young, Jyothish Pari, Pieter Abbeel, Lerrel Pinto.
In the proceedings of the IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS), Kyoto, Japan, October 2022
arXiv 2107.09046

[297] HARP: Autoregressive Latent Video Prediction with High-Fidelity Image Generator,
Younggyo Seo, Kimin Lee, Fangchen Liu, Stephen James, Pieter Abbeel.
In the proceedings of the IEEE International Conference in Image Processing, Bordeaux, France, October 2022
pdf forthcoming

[296] AdaCat: Adaptive Categorical Discretization for Autoregressive Models,
Qiyang (Colin) Li, Ajay Jain, Pieter Abbeel.
In the proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), Eindhoven, The Netherlands, August 2022
pdf forthcoming

[295] Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks,
Litian Liang, Yaosheng Xu, Stephen Mcaleer, Dailin Hu, Alexander Ihler, Pieter Abbeel, Roy Fox.
In the proceedings of the International Conference on Machine Learning (ICML), Baltimore, July 2022

[294] Reinforcement Learning with Action-Free Pre-Training from Videos,
Younggyo Seo, Kimin Lee, Stephen James, Pieter Abbeel.
In the proceedings of the International Conference on Machine Learning (ICML), Baltimore, July 2022
arXiv 2203.13880

[293] Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents,
Wenlong Huang, Pieter Abbeel, Deepak Pathak, Igor Mordatch.
In the proceedings of the International Conference on Machine Learning (ICML), Baltimore, July 2022
arXiv 2201.07207

[292] Zero-Shot Text-Guided Object Generation with Dream Fields,
Ajay Jain, Ben Mildenhall, Jonathan T. Barron, Pieter Abbeel, Ben Poole.
In the proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR), New Orleans, June 2022.
arXiv 2112.01455

[291] Towards more Generalizable One-shot Visual Imitation Learning,
Zhao Mandi, Fangchen Liu, Kimin Lee, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Philadelphia, June 2022.
arXiv 2110.13423

[290] Reward Uncertainty for Exploration in Preference-based Reinforcement Learning,
Xinran Liang, Katherine Shu, Kimin Lee, Pieter Abbeel.
In the proceedings of the 8th International Conference on Learning Representations (ICLR), Virtual, April 2022.
arXiv 2205.12401

[289] SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning,
Jongjin_Park, Younggyo Seo, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee.
In the proceedings of the 8th International Conference on Learning Representations (ICLR), Virtual, April 2022.
arXiv 2203.10050

[288] It Takes Four to Tango: Multiagent Self Play for Automatic Curriculum Generation,
Yuqing Du, Pieter Abbeel, Aditya Grover.
In the proceedings of the 8th International Conference on Learning Representations (ICLR), Virtual, April 2022.
arXiv 2202.10608

[287] Hierarchical Few-Shot Imitation with Skill Transition Models,
Kourosh Hakhamaneshi, Ruihan Zhao, Albert Zhan, Pieter Abbeel, Michael Laskin.
In the proceedings of the 8th International Conference on Learning Representations (ICLR), Virtual, April 2022.
arXiv 2107.08981

[286] Scenic4RL: Programmatic Modeling and Generation of Reinforcement Learning Environments,
Abdus Salam Azad, Edward Kim, Qiancheng Wu, Kimin Lee, Ion Stoica, Pieter Abbeel, Sanjit A. Seshia.
In the proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI), Vancouver, February 2022.
arXiv 2106.10365

[285] Pretrained Transformers as Universal Computation Engines,
Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch.
In the proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI), Vancouver, February 2022.
arXiv 2103.05247

[284] URLB: Unsupervised Reinforcement Learning Benchmark,
Michael Laskin, Denis Yarats, Hao Liu, Kimin Lee, Albert Zhan, Kevin Lu, Catherine Cang, Lerrel Pinto, Pieter Abbeel.
In Neural Information Processing Systems (NeurIPS), Benchmark Track, Virtual, December 2021.
arXiv 2110.15191

[283] B-Pref: Benchmarking Preference-Based Reinforcement Learning,
Kimin Lee, Laura Smith, Anca Dragan, Pieter Abbeel.
In Neural Information Processing Systems (NeurIPS), Benchmark Track, Virtual, December 2021.
arXiv 2111.03026

[282] Mastering Atari Games with Limited Data,
Weirui Ye, Shaohuai Liu, Thanard Kurutach, Pieter Abbeel, Yang Gao.
In Neural Information Processing Systems (NeurIPS), Virtual, December 2021.
arXiv 2111.00210

[281] Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL,
Charles Packer, Pieter Abbeel, Joseph E Gonzalez.
In Neural Information Processing Systems (NeurIPS), Virtual, December 2021.
arXiv 2112.00901

[280] Teachable Reinforcement Learning via Advice Distillation,
Olivia Watkins, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Jacob Andreas.
In Neural Information Processing Systems (NeurIPS), Virtual, December 2021.
arXiv 2203.11197

[279] Decision Transformer: Reinforcement Learning via Sequence Modeling,
Lili Chen*, Kevin Lu*, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch.
In Neural Information Processing Systems (NeurIPS), Virtual, December 2021.
arXiv 2106.01345

[278] Behavior From the Void: Unsupervised Active Pre-Training,
Hao Liu, Pieter Abbeel.
In Neural Information Processing Systems (NeurIPS), Virtual, December 2021.
arXiv 2103.04551

[277] Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings,
Lili Chen, Kimin Lee, Aravind Srinivas, Pieter Abbeel.
In Neural Information Processing Systems (NeurIPS), Virtual, December 2021.
arXiv 2103.02886

[276] Reinforcement Learning with Latent Flow,
Wenling Shang, Xiaofei Wang, Aravind Srinivas, Aravind Rajeswaran, Yang Gao, Pieter Abbeel, Michael Laskin.
In Neural Information Processing Systems (NeurIPS), Virtual, December 2021.
arXiv 2101.01857

[275] Skill Preferences: Learning to Extract and Execute Robotic Skills from Human Feedback,
Xiaofei Wang, Kimin Lee, Kourosh Hakhamaneshi, Pieter Abbeel, Michael Laskin.
In the proceedings of the Conference on Robot Learning (CoRL), London, UK, November 2021.
arXiv 2108.05382

[274] Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemble,
Seunghyun Lee, Younggyo Seo, Kimin Lee, Pieter Abbeel, Jinwoo Shin.
In the proceedings of the Conference on Robot Learning (CoRL), London, UK, November 2021.
arXiv 2107.00591

[273] Contrastive Code Representation Learning,
Paras Jain, Ajay Jain, Tianjun Zhang, Pieter Abbeel, Joseph E. Gonzalez, Ion Stoica.
In the proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Virtual, November 2021.
arXiv 2007.04973

[272] Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis,
Ajay Jain, Matthew Tancik, Pieter Abbeel.
In the proceedings of the International Conference on Computer Vision (ICCV), Virtual, October 2021.
arXiv 2104.00677

[271] AMP: Adversarial Motion Priors for Stylized Physics-Based Character Control,
Xue Bin Peng, Ze Ma, Pieter Abbeel, Sergey Levine, Angjoo Kanazawa.
In the proceedings SIGGRAPH, Virtual, August 2021.
arXiv 2104.02180

[270] PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training,
Kimin Lee*, Laura Smith*, Pieter Abbeel.
In the proceedings of the International Conference on Machine Learning (ICML), Virtual, July 2021.
arXiv 2106.05091

[269] Unsupervised Learning of Visual 3D Keypoints for Sensorimotor Control,
Boyuan Chen, Pieter Abbeel, Deepak Pathak.
In the proceedings of the International Conference on Machine Learning (ICML), Virtual, July 2021.
arXiv 2106.07643

[268] APS: Active Pre-Training with Successor Features,
Hao Liu, Pieter Abbeel.
In the proceedings of the International Conference on Machine Learning (ICML), Virtual, July 2021.
arXiv 2108.13956

[267] MSA Transformer,
Roshan Rao, Jason Liu, Robert Verkuil, Joshua Meier, John Canny, Pieter Abbeel, Tom Sercu, Alexander Rives
In the proceedings of the International Conference on Machine Learning (ICML), Virtual, July 2021.
bioRxiv 2021.02.12.430858

[266] State Entropy Maximization with Random Encoders for Efficient Exploration,
Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee.
In the proceedings of the International Conference on Machine Learning (ICML), Virtual, July 2021.
arXiv 2102.09430

[265] Decoupling Representation Learning from Reinforcement Learning,
Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin.
In the proceedings of the International Conference on Machine Learning (ICML), Virtual, July 2021.
arXiv 2009.08319

[264] SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning,
Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel.
In the proceedings of the International Conference on Machine Learning (ICML), Virtual, July 2021.
arXiv 2007.04938

[263] Bottleneck Transformers for Visual Recognition,
Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani.
In the proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR), Virtual, June 2021.
arXiv 2101.11605

[262] Auto-Tuned Sim-To-Real Transfer, Best Cognitive Robotics Paper Finalist,
Yuqing Du*, Olivia Watkins*, Trevor Darrell, Pieter Abbeel, Deepak Pathak.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Xi'an/Virtual, June 2021.
arXiv 2104.07662

[261] Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots,
Zhongyu Li, Xuxin Cheng, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, Koushil Sreenath.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Xi'an/Virtual, June 2021.
arXiv 2103.14295

[260] LaND: Learning to Navigate from Disengagements, Best Field Robotics Paper Finalist,
Gregory Kahn, Pieter Abbeel, Sergey Levine.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Xi'an/Virtual, June 2021.
arXiv 2010.04689

[259] BADGR: An Autonomous Self-Supervised Learning-Based Navigation System,
Gregory Kahn, Pieter Abbeel, Sergey Levine.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Xi'an/Virtual, June 2021.
arXiv 2002.05700

[258] Learning What To Do by Simulating the Past,
David Lindner, Rohin Shah, Pieter Abbeel, Anca Dragan.
In the proceedings of the 7th International Conference on Learning Representations (ICLR), Virtual, April 2021.
arXiv 2104.03946

[257] Task-Agnostic Morphology Evolution,
Donald J Hejna, Pieter Abbeel, Lerrel Pinto.
In the proceedings of the 7th International Conference on Learning Representations (ICLR), Virtual, April 2021.
arXiv 2102.13100

[256] Reset-Free Lifelong Learning with Skill-Space Planning,
Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch.
In the proceedings of the 7th International Conference on Learning Representations (ICLR), Virtual, April 2021.
arXiv 2012.03548

[255] Self-Supervised Policy Adaptation during Deployment,
Nicklas Hansen, Yu Sun, Pieter Abbeel, Alexei A. Efros, Lerrel Pinto, Xiaolong Wang.
In the proceedings of the 7th International Conference on Learning Representations (ICLR), Virtual, April 2021.
arXiv 2007.04309

[254] Mutual Information-based State-Control for Intrinsically Motivated Reinforcement Learning,
Rui Zhao, Yang Gao, Pieter Abbeel, Volker Tresp, Wei Xu.
In the proceedings of the 7th International Conference on Learning Representations (ICLR), Virtual, April 2021.
arXiv 2103.08107

[253] Efficient Empowerment Estimation for Unsupervised Stabilization,
Ruihan Zhao, Pieter Abbeel, Stas Tiomkin.
In the proceedings of the 7th International Conference on Learning Representations (ICLR), Virtual, April 2021.
arXiv 2007.07356

[252] Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning,
Younggyo Seo, Kimin Lee, Ignasi Clavera, Thanard Kurutach, Jinwoo Shin, Pieter Abbeel.
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2020.
arXiv 2010.13303

[251] AvE: Assistance via Empowerment,
Yuqing Du, Stas Tiomkin, Emre Kiciman, Daniel Polani, Pieter Abbeel, Anca Dragan.
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2020.
arXiv 2006.14796

[250] Denoising Diffusion Probabilistic Models,
Jonathan Ho, Ajay Jain, Pieter Abbeel.
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2020.
arXiv 2006.11239

[249] Automatic Curriculum Learning through Value Disagreement,
Yunzhi Zhang, Pieter Abbeel, Lerrel Pinto.
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2020.
arXiv 2006.09641

[248] Reinforcement Learning with Augmented Data,
Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas.
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2020.
arXiv 2004.14990

[247] Sparse Graphical Memory for Robust Planning,
Michael Laskin, Scott Emmons, Ajay Jain, Thanard Kurutach, Pieter Abbeel, Deepak Pathak.
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2020.
arXiv 2003.06417

[246] Generalized Hindsight for Reinforcement Learning,
Alexander C. Li, Lerrel Pinto, Pieter Abbeel.
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2020.
arXiv 2002.11708

[245] Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model,
Alex X. Lee, Anusha Nagabandi, Pieter Abbeel, Sergey Levine.
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2020.
arXiv 1907.00953

[244] Visual Imitation Made Easy,
Sarah Young, Dhiraj Gandhi, Shubham Tulsiani, Abhinav Gupta, Pieter Abbeel, Lerrel Pinto.
In the proceedings of the Conference on Robot Learning (CoRL), virtual, November 2020.
arXiv 2008.04899

[243] Learning Predictive Representations for Deformable Objects Using Contrastive Estimation,
Wilson Yan, Ashwin Vangipuram, Pieter Abbeel, Lerrel Pinto.
In the proceedings of the Conference on Robot Learning (CoRL), virtual, November 2020.
arXiv 2003.05436

[242] Locally Masked Convolution for Autoregressive Models,
Ajay Jain, Pieter Abbeel, Deepak Pathak.
In the proceedings of the conference on Uncertainty in Artificial Intelligence (UAI), Toronto, Canada, August 2020.
arXiv 2006.12486

[241] Planning to Explore via Self-Supervised World Models,
Ramanan Sekar, Oleh Rybkin, Kostas Daniilidis, Pieter Abbeel, Danijar Hafner, Deepak Pathak.
In the proceedings of the International Conference on Machine Learning (ICML), Virtual/Vienna, Austria, July 2020.
arXiv 2005.05960

[240] Variable Skipping for Autoregressive Range Density Estimation,
Eric Liang*, Zongheng Yang*, Ion Stoica, Pieter Abbeel, Yan Duan, Xi Chen
In the proceedings of the International Conference on Machine Learning (ICML), Virtual/Vienna, Austria, July 2020.
arXiv 2007.05572

[239] Responsive Safety in Reinforcement Learning,
Adam Stooke, Josh Achiam, Pieter Abbeel
In the proceedings of the International Conference on Machine Learning (ICML), Virtual/Vienna, Austria, July 2020.
arXiv 2007.03964

[238] CURL: Contrastive Unsupervised Representations for Reinforcement Learning,
Michael Laskin*, Aravind Srinivas*, Pieter Abbeel.
In the proceedings of the International Conference on Machine Learning (ICML), Virtual/Vienna, Austria, July 2020.
arXiv 2004.04136

[237] Hierarchically Decoupled Imitation for Morphological Transfer,
Donald J. Hejna III, Pieter Abbeel, Lerrel Pinto.
In the proceedings of the International Conference on Machine Learning (ICML), Virtual/Vienna, Austria, July 2020.
arXiv 2003.01709

[236] Hallucinative Topological Memory for Zero-Shot Visual Planning,
Kara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, Aviv Tamar.
In the proceedings of the International Conference on Machine Learning (ICML), Virtual/Vienna, Austria, July 2020.
arXiv 2002.12336

[235] AVID: Learning Multi-Stage Tasks via Pixel-Level Translation of Human Videos,
Laura Smith, Nikita Dhawan, Marvin Zhang, Pieter Abbeel, Sergey Levine.
In the proceedings of Robotics: Science and Systems (R:SS), Corvallis, Oregon, July 2020.
arXiv 1912.04443

[234] Learning to Manipulate Deformable Objects without Demonstrations,
Yilin Wu*, Wilson Yan*, Thanard Kurutach, Lerrel Pinto, Pieter Abbeel.
In the proceedings of Robotics: Science and Systems (R:SS), Corvallis, Oregon, July 2020.
arXiv 1910.13439

[233] Model-Augmented Actor-Critic: Backpropagating through Paths,
Ignasi Clavera*, Yao (Violet) Fu*, Pieter Abbeel.
In the proceedings of the 7th International Conference on Learning Representations (ICLR), Addis Ababa, Ethiopia (virtual), April 2020.
arXiv 2005.08068

[232] Sub-policy Adaptation for Hierarchical Reinforcement Learning,
Alexander C. Li, Carlos Florensa, Ignasi Clavera, Pieter Abbeel.
In the proceedings of the 7th International Conference on Learning Representations (ICLR), Addis Ababa, Ethiopia (virtual), April 2020.
arXiv 1906.05862

[231] Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization,
Paras Jain, Ajay Jain, Aniruddha Nrusimha, Amir Gholami, Pieter Abbeel, Kurt Keutzer, Ion Stoica, Joseph E. Gonzalez.
In the proceedings of the 3rd Conference Machine Learning and Systems (MLSys), Austin, Texas, March 2020
arXiv 1910.02653

[230] Deep Unsupervised Cardinality Estimation
Zongheng Yang, Eric Liang, Amog Kamsetty, Chenggang Wu, Yan Duan, Xi Chen, Pieter Abbeel, Joseph M. Hellerstein, Sanjay Krishnan, Ion Stoica.
In the proceedings of the Very Large Data Bases (VLDB) Endowment, Volume 13, No 3, November 2019.
arXiv 1905.04278

[229] Geometry-Aware Neural Rendering,
Josh Tobin, OpenAI Robotics, Pieter Abbeel
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2019.
arXiv 1911.04554

[228] Plan Arithmetic: Compositional Plan Vectors for Multi-Task Control,
Coline Devin, Daniel Geng, Pieter Abbeel, Trevor Darrell, Sergey Levine
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2019.
arXiv 1910.14033

[227] On the Utility of Learning about Humans for Human-AI Coordination,
Micah Carroll, Rohin Shah, Mark K. Ho, Thomas L. Griffiths, Sanjit A. Seshia, Pieter Abbeel, Anca Dragan
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2019.
arXiv 1910.05789

[226] Evaluating Protein Transfer Learning with TAPE,
Roshan Rao, Nicholas Bhattacharya, Neil Thomas, Yan Duan, Xi Chen, John Canny, Pieter Abbeel, Yun S. Song.
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2019.
arXiv 1906.08230

[225] Goal-conditioned Imitation Learning,
Yiming Ding, Carlos Florensa, Mariano Phielipp, Pieter Abbeel.
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2019.
arXiv 1906.05838

[224] MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies,
Xue Bin (Jason) Peng, Michael Chang, Grace Zhang, Pieter Abbeel, Sergey Levine.
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2019.
arXiv 1905.09808

[223] Compression with Flows via Local Bits-Back Coding,
Jonathan Ho, Evan Lohn, Pieter Abbeel.
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2019.
arXiv 1905.08500

[222] Guided Meta-Policy Search,
Russell Mendonca, Abhishek Gupta, Rosen Kralev, Pieter Abbeel, Sergey Levine, Chelsea Finn.
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2019.
arXiv 1904.00956

[221] Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANs,
Himanshu Sahni, Toby Buckley, Pieter Abbeel, Ilya Kuzovkin.
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2019.
arXiv 1901.11529

[220] BagNet: Berkeley Analog Generator with Layout Optimizer Boosted with Deep Neural Networks,
Kourosh Hakhamaneshi, Nick Werblun, Pieter Abbeel, Vladimir Stojanovic.
In proceedings of the IEEE/ACM International Conference on Computer-Aided Design (ICAD), Westminster, Colorado, November 2019.
arXiv 1907.10515

[219] Asynchronous Methods for Model-Based Reinforcement Learning,
Yunzhi Zhang*, Ignasi Clavera*, Boren Tsai and Pieter Abbeel.
In the proceedings of the Conference on Robot Learning (CORL), Osaka, Japan, November 2019.
arXiv 1910.12453

[218] Blue Gripper: A Robust, Low-Cost, and Force-Controlled Robot Hand,
Menglong Guo, Philipp Wu, Brent Yi, David Gealy, Stephen McKinley, Pieter Abbeel.
In the proceedings of the IEEE 15th International Conference on Automation Science and Engineering, Vancouver, BC, Canada, August 2019.
ieeexplore

[217] Learning Robotic Manipulation through Visual Planning and Acting,
Angelina Wang, Thanard Kurutach, Kara Liu, Pieter Abbeel, Aviv Tamar.
In the proceedings of Robotics: Science and Systems (R:SS), Freiburg, Germany, June 2019.
arXiv 1905.04411

[216] Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design,
Jonathan Ho, Xi (Peter) Chen, Aravind Srinivas, Yan (Rocky) Duan, Pieter Abbeel.
In the proceedings of the International Conference on Machine Learning (ICML), Long Beach, CA, USA, June 2019.
arXiv 1902.00275

[215] On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference,
Rohin Shah, Moah Gundotra, Pieter Abbeel, Anca Dragan.
In the proceedings of the International Conference on Machine Learning (ICML), Long Beach, CA, USA, June 2019.
arXiv 1906.09624

[214] Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables,
Friso H. Kingma, Pieter Abbeel, Jonathan Ho.
In the proceedings of the International Conference on Machine Learning (ICML), Long Beach, CA, USA, June 2019.
arXiv 1905.06845

[213] Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules,
Daniel Ho, Eric Liang, Ion Stoica, Pieter Abbeel, Xi Chen.
In the proceedings of the International Conference on Machine Learning (ICML), Long Beach, CA, USA, June 2019.
arXiv 1905.05393

[212] SOLAR: Deep Structured Latent Representations for Model-Based Reinforcement Learning,
Marvin Zhang, Sharad Vikram, Laura Smith, Pieter Abbeel, Matthew J. Johnson, Sergey Levine.
In the proceedings of the International Conference on Machine Learning (ICML), Long Beach, CA, USA, June 2019.
arXiv 1808.09105

[211] Quasi-Direct Drive for Low-Cost Compliant Robotic Manipulation,
David V. Gealy, Stephen McKinley, Brent Yi, Shiyao Wu, Phillip Robert Downey, Greg Balke, Allan Zhao, Menglong Guo, Rachel Thomasson, Anthony Sinclair, Peter Cuellar, Zoe McCarthy, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, May 2019.
arXiv 1904.03815

[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

[209] Generalization through Simulation: Integrating Simulated and Real Data into Deep Reinforcement Learning for Vision-Based Autonomous Flight,
Katie Kang, Suneel Belkhale, Gregory Kahn, Pieter Abbeel, Sergey Levine.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, May 2019.
arXiv 1902.03701

[208] Reinforcement Learning on Variable Impedance Controller for High-Precision Robotic Assembly,
Jianlan Luo, Eugen Solowjow, Chengtao Wen, Juan Aparicio Ojea, Alice M. Agogino, Aviv Tamar, Pieter Abbeel
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, May 2019.
arXiv 1903.01066

[207] Preference Implicit in the State of the World,
Rohin Shah*, Dmitrii Krasheninnikov*, Jordan Alexander*, Pieter Abbeel, Anca Dragan
In the proceedings of the 7th International Conference on Learning Representations (ICLR), New Orleans, USA, May 2019.
arXiv 1902.04198 (code)

[206] Guiding Policies with Language via Meta-Learning,
John D. Co-Reyes, Abhishek Gupta, Suvansh Sanjeev, Nick Altieri, John DeNero, Pieter Abbeel, Sergey Levine.
In the proceedings of the 7th International Conference on Learning Representations (ICLR), New Orleans, USA, May 2019.
arXiv 1811.07882

[205] ProMP: Proximal Meta-Policy Search,
Jonas Rothfuss*, Dennis Lee*, Ignasi Clavera*, Tamim Asfour, Pieter Abbeel.
In the proceedings of the 7th International Conference on Learning Representations (ICLR), New Orleans, USA, May 2019.
arXiv 1810.06784

[204] Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow,
Xue Bin Peng, Angjoo Kanazawa, Sam Toyer, Pieter Abbeel, Sergey Levine.
In the proceedings of the 7th International Conference on Learning Representations (ICLR), New Orleans, USA, May 2019.
arXiv 1810.00821

[203] Learning to Adapt: Meta-Learning for Model-Based Control,
Ignasi Clavera, Anusha Nagabandi, Ronald S. Fearing, Pieter Abbeel, Sergey Levine, Chelsea Finn.
In the proceedings of the 7th International Conference on Learning Representations (ICLR), New Orleans, USA, May 2019.
arXiv 1803.11347, videos

[202] SFV: Reinforcement Learning of Physical Skills from Videos,
Xue Bin Peng, Angjoo Kanazawa, Jitendra Malik, Pieter Abbeel, Sergey Levine.
In the proceedings of SIGGRAPH ASIA, Tokyo, Japan, December 2018.
arXiv 1810.03599

[201] Learning Plannable Representations with Causal InfoGAN,
Thanard Kurutach, Aviv Tamar, Ge Yang, Stuart Russell, Pieter Abbeel.
In Neural Information Processing Systems (NeurIPS), Montreal, Canada, December 2018.
arXiv 1807.09341

[200] Some Considerations on Learning to Explore via Meta-Reinforcement Learning,
Bradly C. Stadie, Ge Yang, Rein Houthooft, Xi Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever.
In Neural Information Processing Systems (NeurIPS), Montreal, Canada, December 2018.
arXiv 1803.01118

[199] Meta-Reinforcement Learning of Structured Exploration Strategies,
Abhishek Gupta, Russell Mendonca, YuXuan Liu, Pieter Abbeel, Sergey Levine.
In Neural Information Processing Systems (NeurIPS), Montreal, Canada, December 2018.
arXiv 1802.07245

[198] Evolved Policy Gradients,
Rein Houthooft, Richard Y. Chen, Phillip Isola, Bradly C. Stadie, Filip Wolski, Jonathan Ho, Pieter Abbeel.
In Neural Information Processing Systems (NeurIPS), Montreal, Canada, December 2018.
arXiv 1802.04821

[197] An Algorithmic Perspective on Imitation Learning,
Takayuki Osa, Joni Pajarinen, Gerhard Neumann, J. Andrew Bagnell, Pieter Abbeel, Jan Peters.
In Foundations and Trends in Robotics, November 2018.
arXiv 1811.06711

[196] Modular Architecture for StarCraft II with Deep Reinforcement Learning,
Dennis Lee, Haoran Tang, Jeffrey O Zhang, Huazhe Xu, Trevor Darrell, Pieter Abbeel.
In the proceedings of the 14th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE'18), Edmonton, Canada, November 2018.
arXiv 1811.03555

[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

[194] Composable Action-Conditioned Predictors: Flexible Off-Policy Learning for Robot Navigation,
Gregory Kahn, Adam Villaflor, Pieter Abbeel, Sergey Levine.
In the proceedings of the Conference on Robot Learning (CoRL), Zurich, Switzerland, October 2018.
arXiv 1810.07167, video

[193] Establishing Appropriate Trust via Critical States,
Sandy H. Huang, Kush Bhatia, Pieter Abbeel, Anca D. Dragan.
In the proceedings of the IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS), Madrid, Spain, October 2018.
arXiv 1810.08174

[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

[191] DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills,
Xue Bin Peng, Pieter Abbeel, Sergey Levine, Michiel van de Panne.
In the proceedings of SIGGRAPH, Vancouver, Canada, August 2018.
arXiv 1804.02717

[190] Self-Consistent Trajectory Autoencoder: Learning Trajectory Embeddings for Model Based Hierarchical Reinforcement Learning,
John D. Co-Reyes*, YuXuan Liu*, Abhishek Gupta*, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine.
In the proceedings of the International Conference on Machine Learning (ICML), Stockholm, Sweden, July 2018.
arXiv 1806.02813

[189] Latent Space Policies for Hierarchical Reinforcement Learning,
Tuomas Haarnoja, Kristian Hartikainen, Pieter Abbeel, Sergey Levine.
In the proceedings of the International Conference on Machine Learning (ICML), Stockholm, Sweden, July 2018.
arXiv 1804.02809

[188] Universal Planning Networks,
Aravind Srinivas, Allan Jabri, Pieter Abbeel, Sergey Levine, Chelsea Finn.
In the proceedings of the International Conference on Machine Learning (ICML), Stockholm, Sweden, July 2018.
arXiv 1804.00645, videos

[187] Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor,
Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, Sergey Levine.
In the proceedings of the International Conference on Machine Learning (ICML), Stockholm, Sweden, July 2018.
arXiv 1801.01290, github

[186] PixelSNAIL: An Improved Autoregressive Generative Model,
Xi (Peter) Chen, Nikhil Mishra, Mostafa Rohaninejad, Pieter Abbeel.
In the proceedings of the International Conference on Machine Learning (ICML), Stockholm, Sweden, July 2018.
arXiv 1712.09763

[185] Automatic Goal Generation for Reinforcement Learning Agents,
David Held, Xinyang Geng, Carlos Florensa, Pieter Abbeel.
In the proceedings of the International Conference on Machine Learning (ICML), Stockholm, Sweden, July 2018.
arXiv 1705.06366

[184] One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning,
Tianhe Yu*, Chelsea Finn*, Annie Xie, Sudeep Dasari, Tianhao Zhang, Pieter Abbeel, Sergey Levine.
In the proceedings of Robotics: Science and Systems (RSS), Pittsburgh, PA, USA, June 2018.
arXiv 1802.01557, video

[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

[182] Learning with Opponent-Learning Awareness,
Jakob N. Foerster*, Richard Y. Chen*, Maruan Al-Shedivat, Shimon Whiteson, Pieter Abbeel, Igor Mordatch.
In the proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Stockholm, Sweden, July 2018 (arXiv 1709.04326)

[181] Learning Generalized Reactive Policies using Deep Neural Networks,
Edward Groshev, Aviv Tamar, Siddharth Srivastava, Pieter Abbeel.
In the proceedings of the 28th International Conference on Automated Planning and Scheduling (ICAPS), Delft, The Netherlands, June 2018 (arXiv 1708.07280)

[180] Model-Ensemble Trust-Region Policy Optimization,
Thanard Kurutach, Ignasi Clavera, Yan Duan, Aviv Tamar, Pieter Abbeel.
In the proceedings of the 6th International Conference on Learning Representations (ICLR), Vancouver, Canada, April 2018 (arXiv 1802.10592)

[179] A Simple Neural Attentive Meta-Learner,
Nikhil Mishra*, Mostafa Rohaninejad*, Xi (Peter) Chen, Pieter Abbeel.
In the proceedings of the 6th International Conference on Learning Representations (ICLR), Vancouver, Canada, April 2018 (arXiv 1707.03141)

[178] Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines,
Cathy Wu, Aravind Rajeswaran, Yan Duan, Vikash Kumar, Alexandre M Bayen, Sham Kakade, Igor Mordatch, Pieter Abbeel.
In the proceedings of the 6th International Conference on Learning Representations (ICLR), Vancouver, Canada, April 2018 (arXiv 1803.07246)

[177] Meta Learning Shared Hierarchies,
Kevin Frans, Jonathan Ho, Xi Chen, Pieter Abbeel, John Schulman.
In the proceedings of the 6th International Conference on Learning Representations (ICLR), Vancouver, Canada, April 2018 (arXiv 1710.09767)

[176] Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments, Best Paper Award,
Maruan Al-Shedivat, Trapit Bansal, Yuri Burda, Ilya Sutskever, Igor Mordatch, Pieter Abbeel.
In the proceedings of the 6th International Conference on Learning Representations (ICLR), Vancouver, Canada, April 2018 (arXiv 1710.03641, videos)

[175] Parameter Space Noise for Exploration,
Matthias Plappert, Rein Houthooft, Prafulla Dhariwal, Szymon Sidor, Richard Y. Chen, Xi Chen, Tamim Asfour, Pieter Abbeel, Marcin Andrychowicz.
In the proceedings of the 6th International Conference on Learning Representations (ICLR), Vancouver, Canada, April 2018 (arXiv 1706.01905)

[174] Composable Deep Reinforcement Learning for Robotic Manipulation,
Tuomas Haarnoja, Vitchyr Pong, Aurick Zhou, Murtaza Dalal, Pieter Abbeel, Sergey Levine
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, May 2018. (arXiv 1803.06773, videos, code)

[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)

[171] Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation,
Tianhao Zhang, Zoe McCarthy, Owen Jow, Dennis Lee, Xi (Peter) Chen, Ken Goldberg, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, May 2018. (arXiv 1710.04615, videos)

[170] Self-supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigation,
Gregory Kahn, Adam Villaflor, Bosen Ding, Pieter Abbeel, Sergey Levine.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, May 2018. (arXiv 1709.10489)

[169] Overcoming Exploration in Reinforcement Learning with Demonstrations,
Ashvin Nair, Bob McGrew, Marcin Andrychowicz, Wojciech Zaremba, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, May 2018. (arXiv 1709.10089)

[168] Deep Object-Centric Representations for Generalizable Robot Learning,
Coline Devin, Pieter Abbeel, Trevor Darrell, Sergey Levine.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, May 2018. (arXiv 1708.04225)

[167] Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translation,
YuXuan (Andrew) Liu*, Abhishek Gupta*, Pieter Abbeel, Sergey Levine.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, May 2018. (arXiv 1707.03374)

[166] Emergence of Grounded Compositional Language in Multi-Agent Populations,
Igor Mordatch, Pieter Abbeel.
In The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), New Orleans, Louisiana, February 2018. arXiv 1703.04908

[165] Inverse Reward Design,
Dylan Hadfield-Menell, Smitha Milli, Pieter Abbeel, Stuart Russell, Anca Dragan.
In Neural Information Processing Systems (NIPS), Long Beach, CA, December 2017. (arXiv 1711.02827)

[164] Hindsight Experience Replay,
Marcin Andrychowicz, Filip Wolski, Alex Ray, Jonas Schneider, Rachel Fong, Peter Welinder, Bob McGrew, Josh Tobin, Pieter Abbeel, Wojciech Zaremba.
In Neural Information Processing Systems (NIPS), Long Beach, CA, December 2017. (arXiv 1707.01495, videos)

[163] Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments,
Ryan Lowe, Yi Wu, Aviv Tamar, Jean Harb, Pieter Abbeel, Igor Mordatch.
In Neural Information Processing Systems (NIPS), Long Beach, CA, December 2017. (arXiv 1706.02275)

[162] One-Shot Imitation Learning,
Yan (Rocky) Duan, Marcin Andrychowicz, Bradly Stadie, Jonathan Ho, Jonas Schneider, Ilya Sutskever, Pieter Abbeel, Wojciech Zaremba.
In Neural Information Processing Systems (NIPS), Long Beach, CA, December 2017. (arXiv 1703.07326, videos)

[161] #Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning,
Haoran Tang, Rein Houthooft, Davis Foote, Adam Stooke, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel.
In Neural Information Processing Systems (NIPS), Long Beach, CA, December 2017. (arXiv 1611.04717)

[160] One-Shot Visual Imitation Learning via Meta-Learning,
Chelsea Finn*, Tianhe (Kevin) Yu*, Tianhao Zhang, Pieter Abbeel, Sergey Levine.
In the proceedings of the 1st Annual Conference on Robot Learning (CoRL), Mountain View, CA, November 2017. (arXiv 1709.04905, videos)

[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)

[158] Reverse Curriculum Generation for Reinforcement Learning,
Carlos Florensa, David Held, Markus Wulfmeier, Pieter Abbeel.
In the proceedings of the 1st Annual Conference on Robot Learning (CoRL), Mountain View, CA, November 2017. (arXiv 1707.05300)

[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)

[155] The Off-Switch Game,
Dylan Hadfield-Menell, Anca Dragan, Pieter Abbeel, Stuart Russell.
In the proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, August 2017. (arXiv 1611.08219)

[154] Constrained Policy Optimization,
Josh Achiam, David Held, Aviv Tamar, Pieter Abbeel.
In the proceedings of the International Conference on Machine Learning (ICML), Sydney, Australia, August 2017. (arXiv 1705.10528)

[153] Prediction and Control with Temporal Segment Models,
Nikhil Mishra, Pieter Abbeel, Igor Mordatch.
In the proceedings of the International Conference on Machine Learning (ICML), Sydney, Australia, August 2017. (arXiv 1703.04070)

[152] Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks,
Chelsea Finn, Pieter Abbeel, Sergey Levine.
In the proceedings of the International Conference on Machine Learning (ICML), Sydney, Australia, August 2017. (arXiv 1703.03400)

[151] Reinforcement Learning with Deep Energy-Based Policies,
Tuomas Haarnoja*, Haoran Tang*, Pieter Abbeel, Sergey Levine.
In the proceedings of the International Conference on Machine Learning (ICML), Sydney, Australia, August 2017. (arXiv 1702.08165)

[150] Enabling Robots to Communicate their Objectives,
Sandy H. Huang, David Held, Pieter Abbeel, Anca D. Dragan.
In the proceedings of Robotics Science and Systems, Cambridge, MA, July 2017. (arXiv 1702.03465)

[149] Gradescope: A Fast, Flexible, and Fair System for Scalable Assessment of Handwritten Work,
Arjun Singh, Sergey Karayev, Kevin Gutowski, Pieter Abbeel.
In the proceedings of the ACM Conference on Learning at Scale, Cambridge, MA, April 2017. (pdf)

[148] Third Person Imitation Learning,
Bradly Stadie, Pieter Abbeel, Ilya Sutskever.
In the proceedings of the International Conference on Learning Representations (ICLR), Toulon, France, April 2017. (arXiv 1703.01703)

[147] Learning Visual Servoing with Deep Features and Fitted QIteration,
Alex X. Lee, Sergey Levine, Pieter Abbeel.
In the proceedings of the International Conference on Learning Representations (ICLR), Toulon, France, April 2017. (arXiv 1703.11000, videos, code, benchmark)

[146] Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning,
Abhishek Gupta*, Coline Devin*, YuXuan (Andrew) Liu, Pieter Abbeel, Sergey Levine.
In the proceedings of the International Conference on Learning Representations (ICLR), Toulon, France, April 2017. (arXiv 1703.02949)

[145] Stochastic Neural Networks for Hierarchical Reinforcement Learning,
Carlos Florensa Campo, Yan (Rocky) Duan, Pieter Abbeel.
In the proceedings of the International Conference on Learning Representations (ICLR), Toulon, France, April 2017. (arXiv 1704.03012, videos, code)

[144] Generalizing Skills with Semi-Supervised Reinforcement Learning,
Chelsea Finn, Tianhe Yu, Justin Fu, Pieter Abbeel, Sergey Levine.
In the proceedings of the International Conference on Learning Representations (ICLR), Toulon, France, April 2017. (arXiv 1612.00429)

[143] Variational Lossy Autoencoder,
Xi (Peter) Chen, Diederik P. Kingma, Tim Salimans, Yan (Rocky) Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, Pieter Abbeel.
In the proceedings of the International Conference on Learning Representations (ICLR), Toulon, France, April 2017. (arXiv 1611.02731)

[142] Probabilistically Safe Policy Transfer,
David Held, Zoe McCarthy, Michael Zhang, Yide (Fred) Shentu, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 2017. (arXiv 1705.05394)

[141] Combining Self-Supervised Learning and Imitation for Vision-Based Rope Manipulation,
Ashvin Nair, Pulkit Agrawal, Dian Chen, Phillip Isola, Pieter Abbeel, Jitendra Malik, Sergey Levine.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 2017. (arXiv 1703.02018)

[140] Reset-Free Guided Policy Search: Efficient Deep Reinforcement Learning with Stochastic Initial States,
William Montgomery*, Anurag Ajay*, Chelsea Finn, Pieter Abbeel, Sergey Levine.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 2017. (arXiv 1610.01112)

[139] Deep Reinforcement Learning for Tensegrity Robot Locomotion,
Xinyang Geng*, Marvin Zhang*, Jonathan Bruce*, Ken Caluwaerts, Massimo Vespignani, Vytas SunSpiral, Pieter Abbeel, Sergey Levine.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 2017. (arXiv 1609.09049)

[138] Learning from the Hindsight Plan -- Episodic MPC Improvement,
Aviv Tamar, Garrett Thomas, Tianhao Zhang, Sergey Levine, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 2017. (arXiv 1609.09001)

[137] Learning Modular Neural Network Policies for Multi-Task and Multi-Robot Transfer,
Coline Devin*, Abhishek Gupta*, Trevor Darrell, Pieter Abbeel, Sergey Levine.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 2017. (arXiv 1609.07088)

[136] PLATO: Policy Learning using Adaptive Trajectory Optimization,
Gregory Kahn, Tianhao Zhang, Sergey Levine, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 2017. (arXiv 1603.00622)

[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

[134] InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets,
Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, Pieter Abbeel.
In Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016. (arXiv 1606.03657)

[133] Cooperative Inverse Reinforcement Learning,
Dylan Hadfield-Menell, Anca Dragan, Pieter Abbeel, Stuart Russell.
In Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016. (arXiv 1606.03137)

[132] Value Iteration Networks, Best Paper Award,
Aviv Tamar, Yi Wu, Garrett Thomas, Sergey Levine, Pieter Abbeel.
In Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016. (arXiv 1602.02867)

[131] Learning to Poke by Poking: Experiential Learning of Intuitive Physics,
Pulkit Agrawal, Ashvin Nair, Pieter Abbeel, Jitendra Malik, Sergey Levine.
In Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016. (arXiv 1606.07419)

[130] VIME: Variational Information Maximizing Exploration,
Rein Houthooft, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel.
In Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016. (arXiv 1605.09674)

[129] Backprop KF: Learning Discriminative Deterministic State Estimators,
Tuomas Haarnoja, Anurag Ajay, Sergey Levine, Pieter Abbeel.
In Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016. (arXiv 1605.07148)

[128] Combinatorial Energy Learning for Image Segmentation,
Jeremy Maitin-Shepard, Viren Jain, Michal Januszewski, Peter Li, Joergen Kornfeld, Julia Buhmann, Pieter Abbeel.
In Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016. (arXiv 1506.04304)

[127] Data Fitting with Geometric-Programming-Compatible Softmax Functions,
Warren Hoburg, Philippe Kirschen, Pieter Abbeel.
In Optimization and Engineering, pp. 1-22, doi:10.1007/s11081-016-9332-3, August 2016. (online)

[126] One-Shot Learning of Manipulation Skills with Online Dynamics Adaptation and Neural Network Priors,
Justin Fu, Sergey Levine, Pieter Abbeel.
In the proceedings of the 29th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, October 2016. (pdf, arXiv 1509.06841)

[125] Learning Dexterous Manipulation for a Soft Robotic Hand from Human Demonstration,
Abhishek Gupta, Clemens Eppner, Sergey Levine, Pieter Abbeel.
In the proceedings of the 29th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, October 2016. (pdf, arXiv 1603.06348, video)

[124] Sequential Quadratic Programming for Task Plan Optimization,
Dylan Hadfield-Menell, Christopher Lin, Rohan Chitnis, Stuart Russell, Pieter Abbeel.
In the proceedings of the 29th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, October 2016. (pdf)

[123] Occlusion-Aware Multi-Robot 3D Tracking,
Karol Hausman, Gregory Kahn, Sachin Patil, Joerg Mueller, Ken Goldberg, Pieter Abbeel, Gaurav Sukhatme.
In the proceedings of the 29th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, October 2016. (pdf)

[122] Benchmarking Deep Reinforcement Learning for Continuous Control,
Yan Duan, Xi Chen, Rein Houthooft, John Schulman, Pieter Abbeel.
In the proceedings of the International Conference on Machine Learning (ICML), 2016. (arXiv 1604.06778, rllab:code, rllab:docs)

[121] Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization,
Chelsea Finn, Sergey Levine, Pieter Abbeel.
In the proceedings of the International Conference on Machine Learning (ICML), 2016. (arXiv 1603.00448)

[120] Sequential Quadratic Programming for Task Plan Optimization,
Christopher Lin, Dylan Hadfield-Menell, Rohan Chitnis, Stuart Russell and Pieter Abbeel.
To appear in the proceedings of the ICAPS Workshop on Planning and Robotics (PlanRob), London, June 2016.
pdf

[119] End-to-End Training of Deep Visuomotor Policies,
Sergey Levine*, Chelsea Finn*, Trevor Darrell, Pieter Abbeel.
To appear in the Journal of Machine Learning Research (JMLR), 2016. (arXiv 1504.00702, video)

[118] High-Dimensional Continuous Control Using Generalized Advantage Estimation,
John Schulman, Philipp Moritz, Sergey Levine, Michael Jordan, Pieter Abbeel.
In the proceedings of the International Conference on Learning Representations (ICLR), Puerto Rico, May 2016 (arXiv 1506.02438, video)

[117] Combining Model-Based Policy Search with Online Model Learning for Control of Physical Humanoids,
Igor Mordatch, Nikhil Mishra, Clemens Eppner, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA, Stockholm, Sweden, May 2016. (pdf)

[116] Guided Search for Task and Motion Plans Using Learned Heuristics,
Rohan Chitnis, Dylan Hadfield-Menell, Abhishek Gupta, Siddhart Srivastava, Edward Groshev, Christopher Lin, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, May 2016. (pdf, video)

[115] Learning Deep Control Policies for Autonomous Aerial Vehicles with MPC-Guided Policy Search
Tianhao Zhang, Gregory Kahn, Sergey Levine, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, May 2016. (arXiv 1509.06791)

[114] Deep Spatial Autoencoders for Visuomotor Learning
Chelsea Finn, Xin Yu Tan, Yan Duan, Trevor Darrell, Sergey Levine, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, May 2016. (arXiv 1509.06113)

[113] Learning Deep Neural Network Policies with Continuous Memory States
Marvin Zhang, Zoe McCarthy, Chelsea Finn, Sergey Levine, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, May 2016. (arXiv 1507.01273)

[112] Model-based Reinforcement Learning with Parametrized Physical Models and Optimism-Driven Exploration
Christopher Xie, Sachin Patil, Teodor Moldovan, Sergey Levine, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, May 2016. (arXiv 1509.06824)

[111] TSC-DL: Unsupervised Trajectory Segmentation of Multi-Modal Surgical Demonstrations with Deep Learning
Adithyavairavan Murali*, Animesh Garg*, Sanjay Krishnan*, Florian T. Pokorny, Pieter Abbeel, Trevor Darrell, Ken Goldberg.
In the proceedngs of the IEEE International Conference on Robotics and Automation, (ICRA), Stockholm, Sweden. May 2016. (.pdf)

[110] Gradient Estimation Using Stochastic Computation Graphs,
John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel.
In Neural Information Processing Systems (NIPS), Montreal, Canada, December 2015. (arXiv 1506.05254)

[W] Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models,
Bradly C. Stadie, Sergey Levine, Pieter Abbeel.
Presented at NIPS 2015 Workshop on Deep Reinforcement Learning
arXiv 1507.00814

[109] Planning Curvature and Torsion Constrained Ribbons in 3D with Application to Intracavitary Brachytherapy,
Sachin Patil, Jia Pan, Pieter Abbeel, Ken Goldberg.
In IEEE Transactions on Automation Science and Engineering (T-ASE), Volume 12, Issue 4, pp. 1332-1345, October 2015. (pdf)

[108] Leveraging Appearance Priors in Non-Rigid Registration, with Applications to Manipulation of Deformable Objects,
Sandy Huang, Jia Pan, George Mulcaire, Pieter Abbeel.
In the proceedings of the 28th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, September 2015. (pdf)

[107] Learning from Multiple Demonstrations using Trajectory-Aware Non-Rigid Registration with Applications to Deformable Object Manipulation,
Alex Lee, Abhishek Gupta, Henry Lu, Sergey Levine, Pieter Abbeel,
In the proceedings of the 28th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, September 2015. (pdf)

[106] Modular Task and Motion Planning in Belief Space,
Dylan Hadfield-Menell, Edward Groshev, Rohan Chitnis, Pieter Abbeel.
In the proceedings of the 28th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, September 2015. (pdf)

[105] Learning Compound Multi-Step Controllers under Unknown Dynamics,
Weiqiao Han, Sergey Levine, Pieter Abbeel.
In the proceedings of the 28th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, September 2015. (pdf)

[104] Optimized Color Models for High-Quality 3D Scanning,
Karthik Narayan, Pieter Abbeel.
In the proceedings of the 28th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, September 2015. (pdf)

[103] Transition State Clustering: Unsupervised Surgical Trajectory Segmentation for Robot Learning,
Sanjay Krishnan*, Animesh Garg*, Sachin Patil, Colin Lea, Gregory Hager, Pieter Abbeel, Ken Goldberg.
In the proceedings of the 17th International Symposium on Robotics Research (ISRR), Sestri Levanti, Italy, September 2015. (pdf)

[102] Benchmarking in Manipulation Research: The YCB Object and Model Set and Benchmarking Protocols,
Berk Calli, Aaron Walsman, Arjun Singh, Siddhartha Srinivasa, Pieter Abbeel, Aaron Dollar.
In IEEE Robotics and Automation Magazine, 2015. (pdf)

[101] A Disposable Haptic Palpation Probe for Locating Subcutaneous Blood Vessels in Robot-Assisted Minimally Invasive Surgery,
Stephen McKinley, Animesh Garg, Siddarth Sen, Rishi Kapadia, Adithyavairavan Murali, Kirk Nichols, Susan Lim, Sachin Patil, Pieter Abbeel, Allison M. Okamura, Ken Goldberg.
In the proceedings of the IEEE International Conference on Automation Science and Engineering (CASE), Aug. 2015 (pdf)

[100] Multi-Arm Bandit Models for 2D Sample Based Grasp Planning with Uncertainty,
Michael Laskey, Jeff Mahler, Zoe McCarthy, Florian T. Pokorny, Sachin Patil, Jur Van Den Berg, Danica Kragic, Pieter Abbeel, Ken Goldberg.
In the proceedings of the IEEE International Conference on Automation Science and Engineering (CASE), Aug. 2015 (pdf)

[99] The YCB Object and Model Set: Towards Common Benchmarks for Manipulation Research,
Berk Calli, Arjun Singh, Aaron Walsman, Siddhartha Srinivasa, Pieter Abbeel, Aaron M. Dollar.
In the proceedings of the IEEE International Conference on Advanced Robotics (ICAR), Jul. 2015 (pdf)

[98] Information-Theoretic Planning with Trajectory Optimization for Dense 3D Mapping,
Benjamin Charrow, Greg Kahn, Sachin Patil, Sikang Liu, Ken Goldberg, Pieter Abbeel, Nathan Michael, Vijay Kumar.
In the proceedings of Robotics: Science and Systems (RSS), 2015 (pdf)

[97] Trust Region Policy Optimization,
John Schulman, Sergey Levine, Philipp Moritz, Michael I. Jordan, Pieter Abbeel.
In the proceedings of the 32nd International Conference on Machine Learning (ICML), 2015. (pdf, arXiv preprint)

[96] Alpha-Beta Divergences Discover Micro and Macro Structures in Data,
Karthik Narayan, Ali Punjani, Pieter Abbeel.
In the proceedings of the 32nd International Conference on Machine Learning (ICML), 2015 (pdf, code forthcoming)

[95] Deep Learning Helicopter Dynamics Models,
Ali Punjani, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2015. (pdf)

[94] Learning Contact-Rich Manipulation Skills with Guided Policy Search, Best Robotic Manipulation Paper Award,
Sergey Levine, Nolan Wagener, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2015. (pdf)

[93] Beyond Lowest-Warping Cost Action Selection in Trajectory Transfer,
Dylan Hadfield-Menell, Alex Lee, Chelsea Finn, Eric Tzeng, Sandy Huang, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2015. (pdf)

[92] Learning Force-Based Manipulation of Deformable Objects from Multiple Demonstrations,
Alex Lee, Henry Lu, Abhishek Gupta, Sergey Levine, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2015. (pdf)

[91] Physics-Based Trajectory Optimization for Grasping in Cluttered Environments,
Nikita Kitaev, Igor Mordatch, Sachin Patil, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2015. (pdf)

[90] Toward Asymptotically Optimal Motion Planning for Kinodynamic Systems using a Two-Point Boundary Value Problem Solver,
Christopher Xie, Jur van den Berg, Sachin Patil, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2015. (pdf)

[89] Active Exploration using Trajectory Optimization for Robotic Grasping in the Presence of Occlusions,
Gregory Kahn, Peter Sujan, Sachin Patil, Shaunak D. Bopardikar, Julian Ryde, Ken Goldberg, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2015. (pdf)

[88] Range Sensor and Silhouette Fusion for High-Quality 3D Scanning,
Karthik Narayan, James Sha, Arjun Singh, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2015. (pdf)

[87] A Non-Rigid Point and Normal Registration Algorithm with Applications to Learning from Demonstrations,
Alex Lee, Max Goldstein, Shane Barratt, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2015. (pdf)

[86] Optimism-Driven Exploration for Nonlinear Systems,
Teodor Mihai Moldovan, Sergey Levine, Michael I. Jordan, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2015. (pdf)

[85] Learning by Observation for Surgical Subtasks: Multilateral Cutting of 3D Viscoelastic and 2D Orthotropic Tissue Phantoms, Best Medical Robotics Paper Finalist,
Adithyavairavan Murali, Siddarth Sen, Ben Kehoe, Animesh Garg, Seth McFarland, Sachin Patil, Walter Douglas Boyd, Susan Lim, Pieter Abbeel, Ken Goldberg.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2015. (pdf)

[84] GP-GPIS-OPT: Grasp Planning Under Shape Uncertainty Using Gaussian Process Implicit Surfaces and Sequential Convex Programming,
Jeffrey Mahler, Sachin Patil, Ben Kehoe, Jur van den Berg, Matei Ciocarlie, Pieter Abbeel, Ken Goldberg.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2015. (pdf)

[83] A Survey of Research on Cloud Robotics and Automation,
Ben Kehoe, Sachin Patil, Pieter Abbeel, Ken Goldberg.
In IEEE Transaction on Automation Science and Engineering (TASE), April 2015. (pdf)

[82] Deciphering the Role of a Coleopteran Steering Muscle via Free Flight Stimulation,
Hirotaka Sato, Tat Thang Vo Doan, Svetoslav Kolev, Ngoc Anh Huynh, Chao Zhang, Travis L Massey, Joshua van Kleef, Kazuo Ikeda, Pieter Abbeel, Michel M Maharbiz.
In Current Biology, Vol. 25, Issue 6, pp. 798-803, Publisher: Cell Press, March 2015. (pdf)

[81] Tractability of Planning with Loops,
Siddharth Srivastava, Shlomo Zilberstein, Abhishek Gupta, Pieter Abbeel, Stuart Russell.
In the proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), 2015. (pdf)

[80] Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics,
Sergey Levine, Pieter Abbeel.
In Neural Information Processing Systems (NIPS) 27, 2015. (pdf)

[79] Geometric Programming for Aircraft Design Optimization,
Warren Hoburg, Pieter Abbeel.
In AIAA Journal, Vol. 52, No. 11, pp. 2414-2426, Nov. 2014. (pdf)

[78] A Biological Micro Actuator: Graded and Closed-Loop Control of Insect Leg Motion by Electrical Stimulation of Muscles,
Feng Cao, Chao Zhang, Tat Thang Vo Doan, Yao Li, Daniyal Haider Sangi, Jie Sheng Koh, Ngoc Anh Huynh, Mohamed Fareez Bin Aziz, Hao Yu Choo, Kazuo Ikeda, Pieter Abbeel, Michel M. Maharbiz, Hirotaka Sato.
In PLoS ONE 9(8): e105389, doi:10.1371/journal.pone.0105389, published August 20, 2014. (pdf)

[77] Unifying Scene Registration and Trajectory Optimization for Learning from Demonstrations with Application to Manipulation of Deformable Objects,
Alex X. Lee, Sandy H. Huang, Dylan Hadfield-Menell, Eric Tzeng, Pieter Abbeel.
In the proceedings of the 27th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Chicago, USA, September 2014. (pdf)

[76] Optimization-Based Artifact Correction for Electron Microscopy Image Stacks,
Samaneh Azadi, Jeremy Maitin-Shepard, Pieter Abbeel.
In the proceedings of the 13th European Conference on Computer Vision (ECCV), Zurich, Switzerland, September 2014. (pdf, video spotlight, supplementary materials)

[75] Scaling up Gaussian Belief Space Planning through Covariance-Free Trajectory Optimization and Automatic Differentiation,
Sachin Patil, Greg Kahn, Michael Laskey, John Schulman, Ken Goldberg, Pieter Abbeel.
In the proceedings of the 11th International Workshop on the Algorithmic Foundations of Robotics (WAFR), Aug. 2014. (pdf)

[74] Planning Curvature and Torsion Constrained Ribbons in 3D with Application to Intracavitary Brachytherapy,
Sachin Patil, Jia Pan, Pieter Abbeel, Ken Goldberg.
In the proceedings of the 11th International Workshop on the Algorithmic Foundations of Robotics (WAFR), Aug. 2014. (pdf)

[73] Learning Accurate Kinematic Control of Cable-Driven Surgical Robots Using Data Cleaning and Gaussian Process Regression,
Jeffrey Mahler, Sanjay Krishnan, Michael Laskey, Siddarth Sen, Adithyavairavan Murali, Ben Kehoe, Sachin Patil, Jiannan Wang, Mike Franklin, Pieter Abbeel, Ken Goldberg.
In the proceedings of the IEEE International Conference on Automation Science and Engineering (CASE), Taipei, Taiwan, Aug. 2014. (pdf)

[72] Motion Planning with Sequential Convex Optimization and Convex Collision Checking,
John Schulman, Yan Duan, Jonathan Ho, Alex Lee, Ibrahim Awwal, Henry Bradlow, Jia Pan, Sachin Patil, Ken Goldberg, Pieter Abbeel.
In the International Journal of Robotics Research (IJRR), Vol. 33, No. 9, pp. 1251-1270, Aug. 2014. (pdf)

[71] BigBIRD: A Large-Scale 3D Database of Object Instances,
Arjun Singh, James Sha, Karthik Narayan, Tudor Achim, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2014. (pdf)

[70] Combined Task and Motion Planning through an Extensible Planner-Independent Interface Layer,
Siddharth Srivastava, Eugene Fang, Lorenzo Riano, Rohan Chitnis, Stuart Russell, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2014. (pdf, talk video)

[69] Gaussian Belief Space Planning with Discontinuities in Sensing Domains,
Sachin Patil, Yan Duan, John Schulman, Ken Goldberg, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2014. (pdf)

[68] Planning Locally Optimal, Curvature-Constrained Trajectories in 3D using Sequential Convex Optimization,
Yan Duan, Sachin Patil, John Schulman, Ken Goldberg, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2014. (pdf)

[67] Predicting Initialization Effectiveness for Trajectory Optimization,
Jia Pan, Zhuo Chen, Pieter Abbeel.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2014. (pdf, talk video)

[66] Autonomous Multilateral Debridement with the Raven Surgical Robot,
Ben Kehoe, Gregory Kahn, Jeffrey Mahler, Jonathan Kim, Alex Lee, Anna Lee, Keisuke Nakagawa, Sachin Patil, W. Douglas Boyd, Pieter Abbeel, Ken Goldberg.
In the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2014. (pdf)

[65] The Path Inference Filter: Model-Based Low-Latency Map Matching of Probe Vehicle Data,
Tim Hunter, Pieter Abbeel, Alexandre Bayen.
In IEEE Transactions on Intelligent Transportation Systems, Issue 2, pp. 507-529, Apr. 2014. (pdf)

[64] Learning from Demonstrations through the Use of Non-Rigid Registration,
John Schulman, Jonathan Ho, Cameron Lee, Pieter Abbeel.
In the proceedings of the 16th International Symposium on Robotics Research (ISRR), Dec 2013. (pdf)

[63] A Case Study of Trajectory Transfer through Non-Rigid Registration for a Simplified Suturing Scenario,
John Schulman, Ankush Gupta, Sibi Venkatesan, Mallory Tayson-Frederick, Pieter Abbeel.
In the proceedings of the 26th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nov 2013. (pdf, talk video, supplementary materials)

[62] Sigma Hulls for Gaussian Belief Space Planning for Imprecise Articulated Robots amid Obstacles,
Alex Lee, Yan (Rocky) Duan, Sachin Patil, John Schulman, Zoe McCarthy, Jur van den Berg, Ken Goldberg, Pieter Abbeel.
In the proceedings of the 26th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nov 2013. (pdf, talk video)

[61] Grounding Spatial Relations for Human-Robot Interaction,
Sergio Guadarrama, Lorenzo Riano, Dave Golland, Daniel Goehring, Yangqing Jia, Dan Klein, Pieter Abbeel, Trevor Darrell.
In the proceedings of the 26th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nov 2013. (pdf)

[60] Multimodal Blending for High-Accuracy Instance Recognition,
Ziang Xie, Arjun Singh, Justin Uang, Karthik S. Narayan, Pieter Abbeel.
In the proceedings of the 26th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nov 2013. (pdf, talk video)

[59] Large-Scale Estimation in Cyberphysical Systems Using Streaming Data: A Case Study With Arterial Traffic Estimation,
Timothy Hunter, Tathagata Das, Matei Zaharia, Pieter Abbeel, Alexandre M. Bayen.
In IEEE Transactions on Automation Science and Engineering (TASE), Vol. 10, No. 4, pp. 884-898, Oct 2013. (pdf)

[58] Finding Locally Optimal, Collision-Free Trajectories with Sequential Convex Optimization,
John D. Schulman, Jonathan Ho, Alex Lee, Ibrahim Awwal, Henry Bradlow and Pieter Abbeel.
In the proceedings of Robotics: Science and Systems (RSS), Jul 2013. (pdf, videos, code)

[57] Using Classical Planners for Tasks with Continuous Operators in Robotics,
Siddharth Srivastava, Lorenzo Riano, Stuart Russell, Pieter Abbeel.
In the proceedings of the ICAPS Workshop on Planning and Robotics (PlanRob), Jun 2013. (pdf)

[56] Fast Wind Turbine Design via Geometric Programming,
Warren Hoburg and Pieter Abbeel.
In the proceedings of the 9th AIAA MDO Specialist Conference, Boston, MA, Apr. 2013. (pdf)

[55] Tracking Deformable Objects with Point Clouds, Best Vision Paper Award,
John D. Schulman, Alex Lee, Jonathan Ho and Pieter Abbeel.
In the proceedings of the International Conference on Robotics and Automation (ICRA), 2013. (pdf, videos)

[54] Risk Aversion in Markov Decision Processes via Near-Optimal Chernoff Bounds,
Teodor M. Moldovan and Pieter Abbeel.
In Neural Information Processing Systems (NIPS) 25, 2013. (pdf)

[53] Performance analysis and terrain classification for a legged robot over rough terrain,
Fernando L. Garcia Bermudez, Ryan C. Julian, Duncan W. Haldane, Pieter Abbeel, and Ronald S. Fearing.
In the proceedings of the 25th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2012. (pdf)

[52] A Constraint-Aware Motion Planning Algorithm for Robotic Folding of Clothes,
Karthik Lakshmanan, Apoorva Sachdev, Ziang Xie, Dmitry Berenson, Ken Goldberg, Pieter Abbeel.
In the proceedings of the 13th International Symposium on Experimental Robotics (ISER), 2012. (pdf, videos)

[51] Safe Exploration in Markov Decision Processes,
Teodor Moldovan and Pieter Abbeel.
In the proceedings of the 29th International Conference on Machine Learning (ICML), 2012. (pdf)

[50] Geometric Programming for Aircraft Design Optimization,
Warren Hoburg and Pieter Abbeel.
In the proceedings of the 53rd Structures, Structural Dynamics and Materials Conference (SDM) and the 8th AIAA Multidisciplinary Design Optimization Specialist Conference (MDO), 2012. (pdf)

[49] The Path Inference Filter: Model-Based Low-Latency Map Matching of Probe Vehicle Data,
Timothy Hunter, Pieter Abbeel, Alexandre M. Bayen.
In the proceedings of the 10th International Workshop on the Algorithmic Foundations of Robotics (WAFR), Cambridge MA, Jun 2012. (pdf)

[48] Learning the Dynamics of Arterial Traffic from Probe Data using a Dynamic Bayesian Network,
Aude Hofleitner, Ryan Herring, Pieter Abbeel, Alexandre M. Bayen.
In IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2012. (pdf)

[47] A Textured Object Recognition Pipeline for Color and Depth Image Data, Best Vision Paper Finalist,
Jie Tang, Stephen Miller, Arjun Singh, Pieter Abbeel.
In the proceedings of the International Conference on Robotics and Automation (ICRA), 2012. (pdf, talk video)

[46] A Robot Path Planning Framework that Learns from Experience,
Dmitry Berenson, Pieter Abbeel, Ken Goldberg.
In the proceedings of the International Conference on Robotics and Automation (ICRA), 2012. (pdf)

[45] A Geometric Approach to Robotic Laundry Folding,
Stephen Miller, Jur van den Berg, Mario Fritz, Trevor Darrell, Ken Goldberg, Pieter Abbeel
In the International Journal of Robotics Research (IJRR), first published on December 20, 2011 as doi:10.1177/0278364911430417 (pdf)

[44] Scaling the Mobile Millenium System in the Cloud,
Timothy Hunter, Teodor Moldovan, Matei Zaharia, Samy Merzgui, Justin Ma, Michael J. Franklin, Pieter Abbeel, Alexandre M. Bayen
In the proceedings of the ACM Symposium on Cloud Computing (ACM SOCC), 2011. (pdf)

[43] Perception for the Manipulation of Socks,
Ping Chuan Wang, Stephen Miller, Mario Fritz, Trevor Darrell, Pieter Abbeel.
In the proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2011. (pdf, talk video, video)

[42] EG-RRT: Environment-Guided Random Trees for Kinodynamic Motion Planning with Uncertainty and Obstacles,
Leonard Jaillet, Judy Hoffman, Jur van den Berg, Pieter Abbeel, Josep M. Porta, Ken Goldberg.
In the proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2011. (pdf, talk video)

[41] Grasping and Fixturing as Submodular Coverage Problems
John D. Schulman, Ken Goldberg, Pieter Abbeel.
In the proceedings of the 15th International Symposium on Robotics Research (ISRR) , 2011. (pdf, talk video part I, talk video part II, slides)

[40] Motion Planning and Control of Robotic Manipulators on Seaborne Platforms,
Pal J. From, Jan T. Gravdahl, Tommy Lillehagen, Pieter Abbeel.
In Control Engineering Practice, 2011. (pdf)

[39] LQG-MP: Optimized Path Planning for Robots with Motion Uncertainty and Imperfect State Information,
Jur van den Berg, Pieter Abbeel, Ken Goldberg.
In the International Journal of Robotics Research (IJRR), first published on June 3, 2011 as doi:10.1177/0278364911406562. (pdf)

[38] Modeling and Perception of Deformable One-Dimensional Objects,
Shervin Javdani, Sameep Tandon, Jie Tang, James O'Brien, Pieter Abbeel.
In the proceedings of the International Conference on Robotics and Automation (ICRA), 2011. (pdf, talk video)

[37] Parametrized Shape Models for Clothing,
Stephen Miller, Mario Fritz, Trevor Darrell, Pieter Abbeel.
In the proceedings of the International Conference on Robotics and Automation (ICRA), 2011. (pdf, talk video)

[36] Bringing Clothing into Desired Configurations with Limited Perception,
Marco Cusumano-Towner, Arjun Singh, Stephen Miller, James O'Brien, Pieter Abbeel.
In the proceedings of the International Conference on Robotics and Automation (ICRA), 2011. (pdf, talk video)

[35] On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient,
Jie Tang and Pieter Abbeel.
In Neural Information Processing Systems (NIPS) 23, 2011. (pdf)

[34] Gravity-Based Robotic Cloth Folding,
Jur van den Berg, Stephen Miller, Ken Goldberg, Pieter Abbeel.
In The 9th International Workshop on the Algorithmic Foundations of Robotics (WAFR), 2010. (pdf, videos)

[33] LQG-Based Planning, Sensing, and Control of Steerable Needles,
Jur van den Berg, Sachin Patil, Ron Alterovitz, Pieter Abbeel, Ken Goldberg.
In The 9th International Workshop on the Algorithmic Foundations of Robotics (WAFR), 2010. (pdf)

[32] Cyborg Beetles: The Remote Radio Control of Insect Flight,
Hirotaka Sato, Svet Kolev, Nimbus Goehausen, Myo Nyi Nyi, Travis L. Massey, Pieter Abbeel, Michel M. Maharbiz.
In IEEE Sensors, 2010.

[31] LQG-MP: Optimized Path Planning for Robots with Motion Uncertainty and Imperfect State Information,
Jur van den Berg, Pieter Abbeel and Ken Goldberg.
In the proceedings of Robotics: Science and Systems (RSS), 2010. (pdf)

[30] Cloth Grasp Point Detection based on Multiple-View Geometric Cues with Application to Robotic Towel Folding,
Jeremy Maitin-Shepard, Marco Cusumano-Towner, Jinna Lei and Pieter Abbeel.
In the proceedings of the International Conference on Robotics and Automation (ICRA), 2010. (pdf, videos)

[29] Learning Parameterized Maneuvers for Autonomous Helicopter Flight,
Jie Tang, Arjun Singh, Nimbus Goehausen and Pieter Abbeel.
In the proceedings of the International Conference on Robotics and Automation (ICRA), 2010. (pdf)

[28] Superhuman Performance of Surgical Tasks by Robots using Iterative Learning from Human-Guided Demonstrations, Best Medical Robotics Paper Award,
Jur van den Berg, Stephen Miller, Daniel Duckworth, Humphrey Hu, Andrew Wan, Xiao-Yu Fu, Ken Goldberg and Pieter Abbeel.
In the proceedings of the International Conference on Robotics and Automation (ICRA), 2010. (pdf)

[27] On the Influence of Ship Motion Prediction Accuracy on Motion Planning and Control of Robotic Manipulators on Seaborne Platforms,
Pal J. From, Jan T. Gravdahl and Pieter Abbeel.
In the proceedings of the International Conference on Robotics and Automation (ICRA), 2010. (pdf)

[26] Autonomous Helicopter Aerobatics through Apprenticeship Learning,
Pieter Abbeel, Adam Coates and Andrew Y. Ng.
In the International Journal of Robotics Research (IJRR), Volume 29 Issue 13 November 2010. (pdf, videos)

[25] Estimating arterial traffic conditions using sparse probe data,
R. Herring, A. Hofleitner, P. Abbeel, A. Bayen.
13th International IEEE Conference on Intelligent Transportation Systems, Sep. 19-22, 2010, Madeira Island, Portugal

[24] Using Mobile Phones to Forecast Arterial Traffic Through Statistical Learning,
R. Herring, A. Hofleitner, S. Amin, T. Nasr, A. Khalek, P. Abbeel, A. Bayen.
Transportation Research Board 89th Annual Meeting, Washington D.C., January 10-14, 2010

[23i] Apprenticeship learning for helicopter control,
Adam Coates, Pieter Abbeel and Andrew Y. Ng.
In Communications of the ACM , July 2009. (ACM)

[22i] A GPS Software Receiver,
Scott Gleason, Morgan Quigley and Pieter Abbeel.
Chapter 5 in GNSS: Applications and Methods, S. Gleason and D. Gebre-Egziabher (Eds.), 2009.

[21] An Open Source AGPS/DGPS Capable C-coded Software Receiver,
Scott Gleason, Morgan Quigley and Pieter Abbeel.
In Proceedings of the Institute of Navigation, Savannah, GA, 2009.

[20] Apprenticeship Learning for Motion Planning with Application to Parking Lot Navigation,
Pieter Abbeel, Dmitri Dolgov, Andrew Y. Ng and Sebastian Thrun.
In Proceedings of the International Conference on Intellegent RObots and Systems (IROS), 2008. (pdf)

[19] Autonomous Autorotation of an RC Helicopter, IFRR Student Fellowship Award,
Pieter Abbeel, Adam Coates, Timothy Hunter and Andrew Y. Ng.
In 11th International Symposium on Experimental Robotics (ISER) , 2008. (pdf, supplementary material)

[18] Learning for Control from Multiple Demonstrations, Best Paper Award: Best Application Paper,
Adam Coates, Pieter Abbeel and Andrew Y. Ng.
In Proceedings of ICML, 2008. (ps, pdf, supplementary material)

[17] Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion,
J. Zico Kolter, Pieter Abbeel and Andrew Y. Ng.
In NIPS 20, 2008. (ps, pdf)

[16] Max Margin Classification of Data with Absent Features,
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel and Daphne Koller
In Journal of Machine Learning Research (JMLR), 9(Jan):1--21, 2008

[15i] Relational Markov Networks,
B. Taskar, P. Abbeel, M.F. Wong, and D. Koller.
Chapter in Introduction to Statistical Relational Learning, 2007 (L. Getoor and B. Taskar, editors).

[14] Portable GNSS Baseband Logging,
Morgan Quigley, Pieter Abbeel, Dave S. De Lorenzo, Yi Gu, Sara Bolouki, Dennis Akos, and Andrew Y. Ng.
In Institute of Navigation (ION) GNSS Conference, 2007. (pdf)

[13] An Application of Reinforcement Learning to Aerobatic Helicopter Flight,
Pieter Abbeel, Adam Coates, Morgan Quigley and Andrew Y. Ng.
In NIPS 19, 2007. (ps, pdf)

[12] Max-margin classification of incomplete data,
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel and Daphne Koller.
In NIPS 19, 2007. (pdf)

[11] Learning Factor Graphs in Polynomial Time & Sample Complexity,
Pieter Abbeel, Daphne Koller and Andrew Y. Ng.
Journal of Machine Learning Research (JMLR), 7(Aug):1743--1788, 2006. (pdf)

[10] Efficient L1 Regularized Logistic Regression,
SuIn Lee, Honglak Lee, Pieter Abbeel and Andrew Y. Ng.
In Proceedings of AAAI, 2006. (pdf)

[9] Using Inaccurate Models in Reinforcement Learning,
Pieter Abbeel, Morgan Quigley and Andrew Y. Ng.
In Proceedings of ICML, 2006. (ps, pdf, long version: ps pdf)

[8] Learning Vehicular Dynamics, with Application to Modeling Helicopters,
Pieter Abbeel, Varun Ganapathi and Andrew Y. Ng.
In NIPS 18, 2006. (ps, .pdf)

[7] Exploration and Apprenticeship Learning in Reinforcement Learning,
Pieter Abbeel and Andrew Y. Ng.
In Proceedings of ICML, 2005. (ps, pdf, long version: ps, pdf)

[6] Learning Factor Graphs in Polynomial Time & Sample Complexity,
Pieter Abbeel, Daphne Koller and Andrew Y. Ng.
In Proceedings of UAI, 2005. (ps, pdf)

[5] Discriminative training of Kalman filters,
Pieter Abbeel, Adam Coates, Michael Montemerlo, Andrew Y. Ng and Sebastian Thrun.
In Proceedings of RSS, 2005. (ps, pdf)

[4] Learning First Order Markov Models for Control,
Pieter Abbeel and Andrew Y. Ng.
In NIPS 17, 2005. (ps, pdf)

[3] Apprenticeship Learning via Inverse Reinforcement Learning,
Pieter Abbeel and Andrew Y. Ng.
In Proceedings of ICML, 2004. (ps, pdf, supplement: ps , pdf, supplementary webpage here)

[2] Link Prediction in Relational Data,
Ben Taskar, Ming-Fai Wong, Pieter Abbeel and Daphne Koller.
In NIPS 16, 2004. (ps)

[1] Discriminative Probabilistic Models for Relational Data,
Ben Taskar, Pieter Abbeel and Daphne Koller.
In Proceedings of UAI, 2003. (ps)