Papers

Selected Work

CoSTAR: Instructing Collaborative Robots with Behavior Trees and Vision

Our new and improved CoSTAR system, with 3D pose recognition. This paper describes how we built a cross-platform system for authoring complex robot task plans with behavior trees. Winner of the KUKA innovation award.

Presented at ICRA 2017 in Singapore.

Citation:

@article{paxton2017costar,
  title={Co{STAR}: Instructing Collaborative Robots with Behavior Trees and Vision},
  author={Paxton, Chris and Hundt, Andrew and Jonathan, Felix and Guerin, Kelleher and Hager, Gregory D},
  journal={Robotics and Automation (ICRA), 2017 IEEE International Conference on},
  note={Available as arXiv preprint arXiv:1611.06145},
  year={2017}
}

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

Sampling-based task and motion planning using skills learned from expert demonstrations.

Presented at IROS 2016 in Daejeon, Korea.

Citation:

@inproceedings{paxton2016want,
  title={Do what I want, not what I did: Imitation of skills by planning sequences of actions},
  author={Paxton, Chris and Jonathan, Felix and Kobilarov, Marin and Hager, Gregory D},
  booktitle={Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on},
  pages={3778--3785},
  year={2016},
  organization={IEEE}
}

Other Robotics Papers

Previous Work

When working on my Masters, I did some research in early prediction of sepsis before switching directions completely and starting to work on learning task representations for robot motion planning.