Seminars

Spring 2014 GRASP Seminar: Ryan Eustice, University Of Michigan, "SLAM In The Wild: Robust And Persistent Visual SLAM For Autonomous Underwater Hull Inspection"

Presenter: Ryan Eustice (Homepage)

Event Dates:
  Friday February 28, 2014 from 11:00am to 12:00pm

The field of simultaneous localization and mapping (SLAM) has made tremendous progress in the last couple of decades, to the point where we have mature-enough methods and algorithms to explore applications on interesting scales both spatially and temporally.  In this talk we discuss some of our current efforts in deploying large-scale, long-term SLAM systems in real-world field applications, and in particular, our current work in autonomous underwater ship hull inspection.  We will discuss our developments in modeling the visual saliency of underwater imagery for pose-graph SLAM, how this saliency measure can be used within an active SLAM planning paradigm, and our development of generic linear constraints---a principled framework for pose-graph reduction, which is important for controlling multi-session SLAM graph complexity.


Presenter's Biography:

Ryan M. Eustice is an Associate Professor in Naval Architecture & Marine Engineering at the University of Michigan, with additional appointments in the Department of Electrical Engineering and Computer Science, and in the Department of Mechanical Engineering.  He received his PhD in Ocean Engineering in 2005 from the Massachusetts Institute of Technology / Woods Hole Oceanographic Institution Joint Program, and was a postdoctoral scholar at Johns Hopkins University.  His research interests include autonomous navigation and mapping, estimation, computer vision, and perception for mobile robotics, including land/sea/air.  He is an Associate Editor for IEEE Transaction on Robotics, Associate Editor for IEEE Journal of Oceanic Engineering, and recipient of young faculty awards from the Office of Naval Research and the National Science Foundation.  He founded and directs the Perceptual Robotics Laboratory (PeRL) at the University of Michigan.