Dr. Patrick Beeson
Dr. Beeson’s experience lies in integrating cutting-edge robotics algorithms and hardware to create large, robust research platforms. He was the lead software engineer and lead programmer for the Austin Robot Technology autonomous vehicle, which competed in the semifinals of the 2007 DARPA Urban Challenge. More recently he was the integration lead and the software lead for TRACLabs’ 4th place team in the 2012 DARPA Virtual Robotics Challenge and the 6th place team in the DARPA Robotics Challenge 2013 Trials. He has worked on many complex integrated robot systems, including bipedal humanoid robots, small indoor mobile robots, human-assisting wheelchair robots, and urban-driving autonomous vehicles. Specifically, he is known around the world for his research on cognitively-inspired robot perception and reasoning. His past research accomplishments include algorithm for autonomous detection and description of important places in structured environments, a human-inspired hierarchy for robot spatial reasoning, and a real-time implementation for safe 6-DOF navigation using stereo-vision point clouds. In addition to robot navigation, his publications deal with developmental learning for robotics and human-robot interaction. He has worked on DOD projects investigating deployable leader-following, gesture recognition, stereo vision in night-time operation, and visual odometry systems. Prior to his position at TRACLabs, he was a faculty member at the University of Texas at Austin, where he taught undergraduate robotics courses and oversaw an undergraduate robotics research stream for the UT-Austin Freshman Research Initiative.
- 1999 B.S. Computer Science, Tulane University, New Orleans, LA
- 2008 Ph.D. Computer Science, University of Texas at Austin, Austin, TX
P. Beeson and B. Ames. TRAC-IK: An Open-Source Library for Improved Solving of Generic Inverse Kinematics. In Proceedings of the IEEE RAS Humanoids Conference, 2015.
J. James, Y. Weng, S. Hart, P. Beeson, and R. Burridge. Prophetic Goal-Space Planning for Human-in-the-Loop Mobile Manipulation. In Proceedings of the IEEE RAS Humanoids Conference, 2015.
P. Beeson, N. Barrash, and B. Burns. Perception Engine for Activity Recognition and Logging using Manual Procedure Instructions. International Symposium on Artificial Intelligence, Robotics and Automation in Space, 2012.
P. Beeson, J. Modayil, and B. Kuipers. Factoring the mapping problem: Mobile robot map-building in the Hybrid Spatial Semantic Hierarchy. International Journal of Robotics Research, 29(4):428–459, April 2010.
P. Beeson, J. O’Quin, B. Gillan, T. Nimmagadda, M. Ristroph, D. Li, and P. Stone. Multiagent interactions in urban driving. Journal of Physical Agents, 2(1):15–30, March 2008.
P. Beeson, A. Murarka, and B. Kuipers. Adapting proposal distributions for accurate, efficient mobile robot localization. IEEE International Conference on Robotics and Automation (ICRA), 2006.
P. Beeson, N. K. Jong, and B. Kuipers. Towards autonomous topological place detection using the extended Voronoi graph. IEEE International Conference on Robotics and Automation (ICRA), 2005.
B. Kuipers and P. Beeson. Bootstrap learning for place recognition. AAAI Conference on Artificial Intelligence, 2002.