invites you to hear
by
Professor | School of Interactive Computing
Georgia Tech
Thursday, October 31
3 - 4 p.m.
Guggenheim 442
About the Talk:
In robotics and computer vision, simultaneous localization and mapping (SLAM) and structure from motion (SFM) are important and closely related problems. I will review how SLAM, SFM, and other problems in robotics and vision can be posed in terms of factor graphs, which provide a graphical language in which to develop and collaborate on such problems. Many of these ideas are embodied in the Skydio drones, two commercially available, fully autonomous drones I helped develop at a Bay Area startup. I'll present some of our successes as well as more recent work on robotics-centered applications, including motion planning and kino-dynamic planning.
About the Speaker:
Dr. Dellaert does research in the areas of robotics and computer vision, which present some of the most exciting challenges to anyone interested in artificial intelligence. He is especially keen on Bayesian inference approaches to the difficult inverse problems that keep popping up in these areas. In many cases, exact solutions to these problems are intractable, and as such he is interested in examining whether Monte Carlo (sampling-based) approximations are applicable in those cases. Since coming to Georgia Tech Dr. Dellaert has explored the theme of probabilistic, model-based reasoning paired with randomized approximation methods in three main research areas: Advanced sequential Monte Carlo methods, Spatio-Temporal Reconstruction from Images, Simultaneous Localization and Mapping