DANG AT cs.brown.edu

Conference

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

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

[4] Learning robot soccer skills from demonstration.

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

[3] Dogged learning for robots.

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

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

Carsten Magerkurth, Time 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 International Conference on Computer Graphics and Interactive Techniques, Los Angeles, California, 2004.
[ bib | Text ]

Journal

[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), November-December 2006.
[ bib | Text | Url ]

Video

[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, HRI '08: Proceedings of the 3rd ACM/IEEE international conference on Human robot interaction, New York, NY, USA, 2008. ACM.
[ bib | Video | Text ]

Workshop|Symposia

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

Daniel H Grollman and Odest Chadwicke Jenkins.
In IROS workshop on Robotics Challenges for Machine Learning, 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, CAN, December 2007.
[ bib | Video | Poster | Text ]

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

Daniel H Grollman and Odest Chadwicke Jenkins.
In Robotics: Science and Systems - 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 Machine Learning Based Robotics in Unstructured Environments., Whistler, BC, CAN, December 2005.
[ bib | Slides | Text ]

WhitePaper|TechReport

[3] Incremental nonparametric bayesian regression.

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

[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 ]