Publications

PhD Thesis

[1] Teaching old dogs new tricks: Incremental multimap regression for interactive robot learning from demonstration.

Daniel H Grollman.
PhD thesis, Brown University, May 2010.
[ bib | Slides | Text ]

Book Chapters

[1] Chapter: Can We Learn Finite State Machine Robot Controllers from Interactive Demonstration?.

Daniel H Grollman and Odest Chadwicke Jenkins.
From Motor to Interaction Learning in Robots, Springer, 2009.
[ bib | Text ]

Journal Articles

[1] Discovering natural kinds of robot sensory experiences in unstructured environments.

Daniel H. Grollman, Odest Chadwicke Jenkins, and Frank Wood.
Journal of Field Robotics, 23(11-12):1077-1089, November-December 2006.
[ bib | Text | Url ]

Conference Proceedings

[5] Sparse incremental learning for interactive robot control policy estimation.

Daniel H Grollman and Odest Chadwicke Jenkins.
In International Conference on Robotics and Automation, pages 3315-3320, Pasadena, CA, USA, May 2008.
[ bib | Slides | Poster | Text ]

[4] Learning robot soccer skills from demonstration.

Daniel H Grollman and Odest Chadwicke Jenkins.
In International Conference on Development and Learning, pages 276-281, London, UK, July 2007.
[ bib | Teaser | Poster | Text ]

[3] Dogged learning for robots.

Daniel H Grollman and Odest Chadwicke Jenkins.
In International Conference on Robotics and Automation, pages 2483 - 2488, Rome, Italy, April 2007.
[ bib | Video | Slides | Text ]

[2] A component based architecture for distributed, pervasive gaming applications.

Carsten Magerkurth, Timo Engelke, and Dan Grollman.
In ACM SIGCHI International Conference on Advances in Computer Entertainment Technology, Hollywood, CA, USA, June 2006.
[ bib | Text ]

[1] Visualizing deep brain stimulation settings in obsessive compulsive disorder.

David Eigen, Daniel Grollman, David Laidlaw, Benjamin Greenberg, and Erin Einbinder.
In ACM SIGGRAPH International Conference on Computer Graphics and Interactive Techniques, Los Angeles, California, August 2004.
[ bib | Text ]

Videos / Demos

[4] Rgame: Embodied gaming for robot learning by demonstration.

IJCAI 2009 Robot Challenge - LbD, Pasadena, CA, July 2009.
[ bib | Teaser | Text ]

[3] Rgame: Robotic gaming.

ICRA 2009 Robot Challenge - HRI, Kobe, Japan, May 2009.
[ bib | Handout | Poster ]

[2] Game-based learning.

Daniel Byers, Michael Lapping-Carr, Julie Kumar, Thea Hinkle, Dan Grollman, and Chad Jenkins.
AAAI2008 Video Competition, July 2008.
Winner: Best Student Video.
[ bib | Video ]

[1] HRI caught on film 2.

Daniel Byers, Micah Lapping-Carr, Julie Kumar, Theodora Hinkle, Daniel Grollman, and Odest Chadwicke Jenkins.
In Christoph Bartneck, editor, ACM/IEEE International Conference on Human Robot Interaction, Amsterdam, The Netherlands, 2008.
[ bib | Video | Text ]

Workshops / Symposia

[7] Multimap regression for perceptual aliasing in learning finite state machine robot controllers from interactive demonstration.

Daniel H Grollman and Odest Chadwicke Jenkins.
In RSS Workshop on Regression in Robotics, Seattle, Washington, USA, June 2009.
Winner: Best Poster.
[ bib | Slides | Poster | Text ]

[6] Learning multi-objective control policies from demonstration.

Daniel H Grollman and Odest Chadwicke Jenkins.
In IROS workshop on Robotics Challenges for Machine Learning, Nice, France, September 2008.
[ bib | Poster | Text ]

[5] Wiimote interfaces for lifelong robot learning.

Micah Lapping-Carr, Odest Chadwicke Jenkins, Daniel H Grollman, Jonas N Schwertfeger, and Theodora R Hinkle.
In AAAI Spring Symposium, Menlo Park, CA, USA, March 2008.
[ bib | Text ]

[4] (Machine) learning robot control policies.

Daniel H Grollman and Odest Chadwicke Jenkins.
In NIPS Workshop on Robotics Challenges for Machine Learning, Whistler, BC, Canada, December 2007.
[ bib | Video | Poster | Text ]

[3] Learning robot soccer from demonstration: Ball grasping.

Daniel H Grollman and Odest Chadwicke Jenkins.
In R:SS Workshop on Robot Manipulation: Sensing and Adapting to the Real World, Atlanta, GA, USA, June 2007.
[ bib | Poster | Text ]

[2] Discovering natural kinds of robot sensory experiences in unstructured environments.

Daniel H Grollman, Odest Chadwicke Jenkins, and Frank Wood.
In North East Student Colloquium on Artificial Intelligence, Ithica, NY, USA, April 2006.
[ bib | Slides | Text ]

[1] Discovering natural kinds of robot sensory experiences in unstructured environments.

Daniel H. Grollman, Odest Chadwicke Jenkins, and Frank Wood.
In NIPS Workshop on Machine Learning Based Robotics in Unstructured Environments., Whistler, BC, Canada, December 2005.
[ bib | Slides | Text ]

White Papers / Technical Reports

[4] RGame: Embodied Gaming for Robot Learning by Demonstration.

Daniel H. Grollman, Odest Chadwicke Jenkins, and Jesse Butterfield.
Technical report, AAAI, 2009.
[ bib | Text ]

[3] Incremental Nonparametric Bayesian Regression.

Frank Wood, Daniel H. Grollman, Katherine A. Heller, Odest C. Jenkins, and Michael Black.
Technical Report CS-08-07, Brown University Department of Computer Science, 2008.
[ bib | Text ]

[2] Extensible data-driven classification of robot sensor data.

Daniel H Grollman, Odest Chadwicke Jenkins, and Frank Wood.
Technical report, Brown University Department of Computer Science, 2005.
[ bib | Poster | Text | Url ]

[1] Astrology: The study of astro teller.

Stuart Andrews, Lijuan Cai, David Gondek, Amy Greenwald, Daniel Grollman, Arni Mar Jonsson, Keith Hall, Matthew Lease, Bryant Ng, John Raiti, Victoria Sweetser, and Jenine Turner.
In International Conference on Machine Learning Physiological Modeling Contest, 2004.
[ bib | Text | Url ]

Other Talks

[8] Robots, and Learning, and the Future! Oh my!.

Applied Minds, Glendale, CA, July 2009.
[ bib | Slides ]

[7] Learning multimap robot control policies from demonstration.

University of Massachusetts, Amherst, Amherst, MA, April 2009.
[ bib | Slides ]

[6] Multimap control policies.

Washington University in St. Louis, St. Louis, February 2009.
[ bib | Slides ]

[5] Learning from multimap demonstration.

Harvard Artificial Intelligence Research Group, Boston, November 2008.
[ bib | Slides ]

[4] Sparse incremental learning for interactive robot control policy estimation.

New England Manipulation Symposium, Providence, RI, May 2008.
[ bib | Slides ]

[3] Interactive robot learning with statistical regression.

HRI Young Pioneers Workshop, Amsterdam, March 2008.
[ bib | Slides ]

[2] Learning robot soccer skills from demonstration.

New England Manipulation Symposium, Boston, June 2007.
[ bib | Slides ]

[1] Dogged learning for robots.

HRI Young Pioneers Workshop, Washington, D.C., USA, March 2007.
[ bib ]