Title
An on-board vision sensor system for small unmanned vehicle applications
Abstract
This paper describes an on-board vision sensor system that is developed specifically for small unmanned vehicle applications. For small vehicles, vision sensors have many advantages, including size, weight, and power consumption, over other sensors such as radar, sonar, and laser range finder, etc. A vision sensor is also uniquely suited for tasks such as target tracking and recognition that require visual information processing. However, it is difficult to meet the computing needs of real-time vision processing on a small robot. In this paper, we present the development of a field programmable gate array-based vision sensor and use a small ground vehicle to demonstrate that this vision sensor is able to detect and track features on a user-selected target from frame to frame and steer the small autonomous vehicle towards it. The sensor system utilizes hardware implementations of the rank transform for filtering, a Harris corner detector for feature detection, and a correlation algorithm for feature matching and tracking. With additional capabilities supported in software, the operational system communicates wirelessly with a base station, receiving commands, providing visual feedback to the user and allowing user input such as specifying targets to track. Since this vision sensor system uses reconfigurable hardware, other vision algorithms such as stereo vision and motion analysis can be implemented to reconfigure the system for other real-time vision applications.
Year
DOI
Venue
2012
10.1007/s00138-012-0413-9
Mach. Vis. Appl.
Keywords
Field
DocType
FPGA,Real-time vision,Small autonomous vehicles,Target tracking,Motion analysis,Pattern matching
Computer vision,Corner detection,Machine vision,Computer science,Stereopsis,Field-programmable gate array,Sonar,Artificial intelligence,Motion analysis,Robot,Reconfigurable computing
Journal
Volume
Issue
ISSN
23
3
0932-8092
Citations 
PageRank 
References 
5
0.42
14
Authors
3
Name
Order
Citations
PageRank
Beau J. Tippetts11127.62
Dah-Jye Lee242242.05
James K. Archibald3632161.01