Vision-based localization in urban environments

Michael McHenry; Yang Cheng; Larry Matthies

doi:10.1117/12.603973

27 May 2005 Vision-based localization in urban environments

Michael McHenry, Yang Cheng, Larry Matthies

Proceedings Volume 5804, Unmanned Ground Vehicle Technology VII; (2005) https://doi.org/10.1117/12.603973
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

As part of DARPA's MARS2020 program, the Jet Propulsion Laboratory has developed a vision-based system for localization in urban environments that requires neither GPS nor active sensors. System hardware consists of a pair of small FireWire cameras and a standard Pentium-based computer. The inputs to the software system consist of: 1) a crude grid-based map describing the positions of buildings, 2) an initial estimate of robot location and 3) the video streams produced by the stereo pair. At each step during the traverse the system: captures new image data, finds image features hypothesized to lie on the outside of a building, computes the range to those features, determines an estimate of the robot's motion since the previous step and combines that data with the map to update a probabilistic representation of the robot's location. This probabilistic representation allows the system to simultaneously represent multiple possible locations. For our testing, we have derived the a priori map manually using non-orthorectified overhead imagery, although this process could be automated. The software system consists of three primary components. The first is a stereo-based visual odometry system that calculates the 6-degree of freedom camera motion between sequential frames. The second component uses a set of heuristics to identify straight-line segments that are likely to be part of a building exterior. Ranging to these straight-line features is computed using binocular or wide-baseline stereo. The resulting features and the associated range measurements are fed to the third software component, a particle-filter based localization system. This system uses the map and the most recent results from the first two to update the estimate of the robot's location. This report summarizes the design of both the hardware and software and describes the results of applying the system to the global localization of a camera system over an approximately half-kilometer traverse across JPL's Pasadena campus.

Citation Download Citation

Michael McHenry, Yang Cheng, and Larry Matthies "Vision-based localization in urban environments", Proc. SPIE 5804, Unmanned Ground Vehicle Technology VII, (27 May 2005); https://doi.org/10.1117/12.603973

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available