CMU talk: 3-D Stereo Vision SLAM for Autonomous Mapping and Navigation (live demonstration)

FRC Seminar

3-D Stereo Vision SLAM for Autonomous Mapping and Navigation (live demonstration)

Pearse Ffrench
Project Manager and Senior Technical Staff Member
Vision Robotics
San Diego, CA


Thursday, April 2nd, 2009

Vision Robotics has developed a 3-D stereo vision SLAM, visual odometry, object identification, and tracking system for autonomous robots. The current applications include an autonomous canister style vacuum cleaner and a sensor system for military UGV's. The presentation will describe the 3-D stereo vision SLAM algorithms including the stereo vision processing, particle based localization, and 3-D map generation. It will conclude with a demonstration of the 3-D stereo vision SLAM sensor system on a prototype Autonomous Mapping Vehicle (AMV) being developed for SPAWAR System Center San Diego. The current prototype uses a Segway RMP-50 as a base platform, has four stereo camera pairs, and maps at over 100 square feet per minute with speeds over 2 mph. An external link via 802.11N to a laptop provides for start/stop/pause control and real-time display of the map and pose data. The AMV will autonomously move throughout an area, and when it has finished exploring the complete area, it will return to the starting location.

Speaker Bio
Pearse received the B.S. in electrical engineering from Massachusetts Institute of Technology in 1989 and the M.S. in electrical engineering from the University of California, San Diego in 1994. Pearse Ffrench is a project manager and senior technical staff member at Vision Robotics. He has been developing 3-D stereo vision SLAM and tracking algorithms at Vision Robotics for the past eight years. Previously, he was the founder and CTO of Digital Transport Systems, a communications test equipment company which was acquired by Wavetek Wandel Golterman in 1998. From 1989 to 1994, he was the lead engineer for Advanced Processing Laboratories on several Navy projects involving underwater acoustics and signal processing.