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Alternative Paths Planner (APP) for Provably Fixed-time Manipulation Planning in Semi-structured Environments

Dec 29, 2020
Fahad Islam, Chris Paxton, Clemens Eppner, Bryan Peele, Maxim Likhachev, Dieter Fox


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Reactive Human-to-Robot Handovers of Arbitrary Objects

Nov 17, 2020
Wei Yang, Chris Paxton, Arsalan Mousavian, Yu-Wei Chao, Maya Cakmak, Dieter Fox


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Sim-to-Real Task Planning and Execution from Perception via Reactivity and Recovery

Nov 17, 2020
Shohin Mukherjee, Chris Paxton, Arsalan Mousavian, Adam Fishman, Maxim Likhachev, Dieter Fox

* Under review 

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Human Grasp Classification for Reactive Human-to-Robot Handovers

Mar 12, 2020
Wei Yang, Chris Paxton, Maya Cakmak, Dieter Fox


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Transferable Task Execution from Pixels through Deep Planning Domain Learning

Mar 08, 2020
Kei Kase, Chris Paxton, Hammad Mazhar, Tetsuya Ogata, Dieter Fox

* 7 pages, 6 figures. Conference paper accepted in International conference on Robotics and Automation (ICRA) 2020 

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6-DOF Grasping for Target-driven Object Manipulation in Clutter

Dec 08, 2019
Adithyavairavan Murali, Arsalan Mousavian, Clemens Eppner, Chris Paxton, Dieter Fox


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Motion Reasoning for Goal-Based Imitation Learning

Nov 13, 2019
De-An Huang, Yu-Wei Chao, Chris Paxton, Xinke Deng, Li Fei-Fei, Juan Carlos Niebles, Animesh Garg, Dieter Fox


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Online Replanning in Belief Space for Partially Observable Task and Motion Problems

Nov 11, 2019
Caelan Reed Garrett, Chris Paxton, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Dieter Fox


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Conditional Driving from Natural Language Instructions

Oct 16, 2019
Junha Roh, Chris Paxton, Andrzej Pronobis, Ali Farhadi, Dieter Fox

* Accepted by the 3rd Conference on Robot Learning, Osaka, Japan (CoRL 2019) 

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Trajectory Optimization for Coordinated Human-Robot Collaboration

Oct 10, 2019
Adam Fishman, Chris Paxton, Wei Yang, Nathan Ratliff, Dieter Fox

* 3 figures, 7 pages 

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"Good Robot!": Efficient Reinforcement Learning for Multi-Step Visual Tasks via Reward Shaping

Sep 25, 2019
Andrew Hundt, Benjamin Killeen, Heeyeon Kwon, Chris Paxton, Gregory D. Hager

* 7 pages, 6 figures, code is available at https://github.com/jhu-lcsr/good_robot 

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Representing Robot Task Plans as Robust Logical-Dynamical Systems

Aug 05, 2019
Chris Paxton, Nathan Ratliff, Clemens Eppner, Dieter Fox

* 9 pages, extended version of IROS 2019 paper 

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Prospection: Interpretable Plans From Language By Predicting the Future

Mar 20, 2019
Chris Paxton, Yonatan Bisk, Jesse Thomason, Arunkumar Byravan, Dieter Fox

* Accepted to ICRA 2019; extended version with appendix containing additional results 

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The CoSTAR Block Stacking Dataset: Learning with Workspace Constraints

Mar 12, 2019
Andrew Hundt, Varun Jain, Chia-Hung Lin, Chris Paxton, Gregory D. Hager

* This is a major revision refocusing the topic towards the JHU CoSTAR Block Stacking Dataset, workspace constraints, and a comparison of HyperTrees with hand-designed algorithms. 12 pages, 10 figures, and 3 tables 

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Evaluating Methods for End-User Creation of Robot Task Plans

Nov 06, 2018
Chris Paxton, Felix Jonathan, Andrew Hundt, Bilge Mutlu, Gregory D. Hager

* 2018 IEEE Conference on Intelligent Robots and Systems 
* 7 pages; IROS 2018 

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Training Frankenstein's Creature to Stack: HyperTree Architecture Search

Oct 27, 2018
Andrew Hundt, Varun Jain, Chris Paxton, Gregory D. Hager

* Video is at https://sites.google.com/view/hypertree-renas . 7 pages, 6 figures, and 2 tables 

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Visual Robot Task Planning

Mar 30, 2018
Chris Paxton, Yotam Barnoy, Kapil Katyal, Raman Arora, Gregory D. Hager

* 8 pages, IEEE format, currently in review 

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Occupancy Map Prediction Using Generative and Fully Convolutional Networks for Vehicle Navigation

Mar 06, 2018
Kapil Katyal, Katie Popek, Chris Paxton, Joseph Moore, Kevin Wolfe, Philippe Burlina, Gregory D. Hager

* 7 pages 

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Learning to Imagine Manipulation Goals for Robot Task Planning

Nov 09, 2017
Chris Paxton, Kapil Katyal, Christian Rupprecht, Raman Arora, Gregory D. Hager


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Temporal and Physical Reasoning for Perception-Based Robotic Manipulation

Oct 11, 2017
Felix Jonathan, Chris Paxton, Gregory D. Hager

* 8 pages, currently in peer review 

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User Experience of the CoSTAR System for Instruction of Collaborative Robots

Mar 23, 2017
Chris Paxton, Felix Jonathan, Andrew Hundt, Bilge Mutlu, Gregory D. Hager

* 8 pages, currently in peer review. Video: https://www.youtube.com/watch?v=uf_3P6TmVrQ 

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Combining Neural Networks and Tree Search for Task and Motion Planning in Challenging Environments

Mar 22, 2017
Chris Paxton, Vasumathi Raman, Gregory D. Hager, Marin Kobilarov

* 8 pgs, currently in peer review. Video: https://youtu.be/MM2U_SGMtk8 

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Do What I Want, Not What I Did: Imitation of Skills by Planning Sequences of Actions

Dec 05, 2016
Chris Paxton, Felix Jonathan, Marin Kobilarov, Gregory D Hager

* 8 pages, published at IROS 2016 

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CoSTAR: Instructing Collaborative Robots with Behavior Trees and Vision

Nov 18, 2016
Chris Paxton, Andrew Hundt, Felix Jonathan, Kelleher Guerin, Gregory D. Hager


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Towards Robot Task Planning From Probabilistic Models of Human Skills

Feb 15, 2016
Chris Paxton, Marin Kobilarov, Gregory D. Hager

* 8 pages, presented at AAAI 2016 PlanHS workshop 

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