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 | Apprentice | Optimization-based Planning | Belief Space Planning | Hierarchical Planning | Perception | Deformable Objects | Medical Robotics | Helicopter | Connectomics ]
Pre-prints
Publications

bibtex

[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)

[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)

[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)

[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)

[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)

[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)

[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)

[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)

[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)

[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)

[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)