Chris Paxton
Title
Cited by
Cited by
Year
Developing predictive models using electronic medical records: challenges and pitfalls
C Paxton, A Niculescu-Mizil, S Saria
AMIA Annual Symposium Proceedings 2013, 1109, 2013
972013
Costar: Instructing collaborative robots with behavior trees and vision
C Paxton, A Hundt, F Jonathan, K Guerin, GD Hager
2017 IEEE international conference on robotics and automation (ICRA), 564-571, 2017
872017
Combining neural networks and tree search for task and motion planning in challenging environments
C Paxton, V Raman, GD Hager, M Kobilarov
Intelligent Robots and Systems (IROS), 2017 IEEE/RSJ International Conference on, 2017
832017
A framework for end-user instruction of a robot assistant for manufacturing
KR Guerin, C Lea, C Paxton, GD Hager
2015 IEEE international conference on robotics and automation (ICRA), 6167-6174, 2015
792015
An incremental approach to learning generalizable robot tasks from human demonstration
C Paxton, GD Hager, L Bascetta
2015 IEEE international conference on robotics and automation (ICRA), 5616-5621, 2015
402015
6-dof grasping for target-driven object manipulation in clutter
A Murali, A Mousavian, C Eppner, C Paxton, D Fox
2020 IEEE International Conference on Robotics and Automation (ICRA), 6232-6238, 2020
322020
Visual robot task planning
C Paxton, Y Barnoy, K Katyal, R Arora, GD Hager
2019 international conference on robotics and automation (ICRA), 8832-8838, 2019
302019
Representing robot task plans as robust logical-dynamical systems
C Paxton, N Ratliff, C Eppner, D Fox
arXiv preprint arXiv:1908.01896, 2019
212019
Do what I want, not what I did: Imitation of skills by planning sequences of actions
C Paxton, F Jonathan, M Kobilarov, GD Hager
Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International …, 2016
212016
Evaluating methods for end-user creation of robot task plans
C Paxton, F Jonathan, A Hundt, B Mutlu, GD Hager
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018
182018
Semi-autonomous telerobotic assembly over high-latency networks
J Bohren, C Paxton, R Howarth, GD Hager, LL Whitcomb
2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI …, 2016
172016
Online replanning in belief space for partially observable task and motion problems
CR Garrett, C Paxton, T Lozano-Pérez, LP Kaelbling, D Fox
2020 IEEE International Conference on Robotics and Automation (ICRA), 5678-5684, 2020
162020
Uncertainty-aware occupancy map prediction using generative networks for robot navigation
K Katyal, K Popek, C Paxton, P Burlina, GD Hager
2019 International Conference on Robotics and Automation (ICRA), 5453-5459, 2019
162019
Prospection: Interpretable Plans From Language By Predicting the Future
C Paxton, Y Bisk, J Thomason, A Byravan, D Fox
2019 International Conference on Robotics and Automation (ICRA), 2019
162019
Trajectory generation using temporal logic and tree search
M Kobilarov, T Caldwell, V Raman, C Paxton, JMP Kiiski, JL Askeland, ...
US Patent 10,133,275, 2018
132018
Human grasp classification for reactive human-to-robot handovers
W Yang, C Paxton, M Cakmak, D Fox
arXiv preprint arXiv:2003.06000, 2020
122020
Conditional driving from natural language instructions
J Roh, C Paxton, A Pronobis, A Farhadi, D Fox
Conference on Robot Learning, 540-551, 2020
82020
Training frankenstein’s creature to stack: Hypertree architecture search
A Hundt, V Jain, C Paxton, GD Hager
arXiv preprint arXiv:1810.11714 1 (2), 2018
7*2018
“Good Robot!”: Efficient Reinforcement Learning for Multi-Step Visual Tasks with Sim to Real Transfer
A Hundt, B Killeen, N Greene, H Wu, H Kwon, C Paxton, GD Hager
IEEE Robotics and Automation Letters 5 (4), 6724-6731, 2020
62020
User experience of the CoSTAR system for instruction of collaborative robots
C Paxton, F Jonathan, A Hundt, B Mutlu, GD Hager
arXiv preprint arXiv:1703.07890, 2017
62017
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