NDLI: Vision based object identification and tracking for mobile robot visual servo control

Content Provider	IEEE Xplore Digital Library
Author	Haoxiang Lang Ying Wang de Silva, C.W.
Copyright Year	2010
Description	Author affiliation: Division of Engineering, Southern Polytechnic State University, Marietta, GA 30060 USA (Ying Wang) \|\| Mechanical Engineering Department, the University of British Columbia, Vancouver, V6T 1Z4, Canada (Haoxiang Lang; de Silva, C.W.)
Abstract	A key problem of an Image Based Visual Servo (IBVS) system is how to identify and track objects in a series of images. In this paper, a scale-invariant image feature detector and descriptor, which is called the Scale-Invariant Feature Transform (SIFT), is utilized to achieve robust object tracking in terms of rotation, scaling and changes of illumination. To the best of our knowledge, this paper represents the first work to apply the SIFT algorithm to visual servoing for robust mobile robot tracking. First, a SIFT method is used to generate the feature points of an object template and a series of images are acquired while the robot is moving. Second, a feature matching method is applied to match the features between the template and the images. Finally, based on the locations of the matched feature points, the location of the object is approximated in the images of camera views. This algorithm of object identification and tracking is applied in an Image-Based Visual Servo (IBVS) system for providing the location of the object in the feedback loop. In particular, the IBVS controller determines the desired wheel speeds ω_1 and ω_2 of a wheeled mobile robot, and accordingly commands the low-level controller of the robot. Then the IBVS controller drives the robot toward a target object until the location of the object reaches the desired location in the image. The IBVS system is implemented and tested in a mobile robot with an on-board camera, in our laboratory. The results are used to demonstrate satisfactory performance of the object identification and tracking algorithm. Furthermore, a MATLAB simulation is used to confirm the stability and convergence of the IBVS controller.
Starting Page	92
Ending Page	96
File Size	679618
Page Count	5
File Format	PDF
ISBN	9781424451951
ISSN	19483457
DOI	10.1109/ICCA.2010.5524180
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-06-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mobile robots Servosystems Servomechanisms Robustness Robot vision systems Cameras Robot control Computer vision Object detection Detectors
Content Type	Text
Resource Type	Article

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