Gabe's core interest is in probabilistic perception algorithms and estimation theory that enable long-term autonomous operation of mobile robotic systems, particularly in unknown environments. He has extensive experience with vision based, real-time localization and mapping systems, and is interested in fundamental understanding of sufficient statistics that can be used to represent the state of the world. His research uses real-time, embodied robot systems equipped with a variety of sensors -- including lasers, cameras, inertial sensors, etc. -- to advance and validate algorithms and knowledge representations that are useful for enabling long-term autonomous operation.
keywords
Mobile robotics, computer vision, estimation theory, field robotics
Light Source Estimation in Synthetic Images.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
887-893.
2016
Closing Loops Without Places.
Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems.
3738-3744.
2010
