Correlation-based visual odometry for ground vehicles

Nourani-Vatani, Navid and Borges, Paulo Vinicius Koerich (2011) Correlation-based visual odometry for ground vehicles. Journal of Field Robotics, 28 5: 742-768. doi:10.1002/rob.20407


Author Nourani-Vatani, Navid
Borges, Paulo Vinicius Koerich
Title Correlation-based visual odometry for ground vehicles
Journal name Journal of Field Robotics   Check publisher's open access policy
ISSN 1556-4959
1556-4967
Publication date 2011-09-01
Sub-type Article (original research)
DOI 10.1002/rob.20407
Open Access Status Not yet assessed
Volume 28
Issue 5
Start page 742
End page 768
Total pages 27
Place of publication Hoboken, NJ, United States
Publisher John Wiley & Sons
Language eng
Abstract Reliable motion estimation is a key component for autonomous vehicles. We present a visual odometry method for ground vehicles using template matching. The method uses a downward-facing camera perpendicular to the ground and estimates the motion of the vehicle by analyzing the image shift from frame to frame. Specifically, an image region (template) is selected, and using correlation we find the corresponding image region in the next frame. We introduce the use of multitemplate correlation matching and suggest template quality measures for estimating the suitability of a template for the purpose of correlation. Several aspects of the template choice are also presented. Through an extensive analysis, we derive the expected theoretical error rate of our system and show its dependence on the template window size and image noise. We also show how a linear forward prediction filter can be used to limit the search area to significantly increase the computation performance. Using a single camera and assuming an Ackerman-steering model, the method has been implemented successfully on a large industrial forklift and a 4×4 vehicle. Over 6 km of field trials from our industrial test site, an off-road area and an urban environment are presented illustrating the applicability of the method as an independent sensor for large vehicle motion estimation at practical velocities.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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