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Sensors 2015, 15(10), 26063-26084; doi:10.3390/s151026063

A Novel Robot Visual Homing Method Based on SIFT Features

College of Automation, Harbin Engineering University, Harbin 150001, China
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Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 2 July 2015 / Revised: 30 September 2015 / Accepted: 9 October 2015 / Published: 14 October 2015
(This article belongs to the Section Physical Sensors)
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Abstract

Warping is an effective visual homing method for robot local navigation. However, the performance of the warping method can be greatly influenced by the changes of the environment in a real scene, thus resulting in lower accuracy. In order to solve the above problem and to get higher homing precision, a novel robot visual homing algorithm is proposed by combining SIFT (scale-invariant feature transform) features with the warping method. The algorithm is novel in using SIFT features as landmarks instead of the pixels in the horizon region of the panoramic image. In addition, to further improve the matching accuracy of landmarks in the homing algorithm, a novel mismatching elimination algorithm, based on the distribution characteristics of landmarks in the catadioptric panoramic image, is proposed. Experiments on image databases and on a real scene confirm the effectiveness of the proposed method. View Full-Text
Keywords: visual homing; mismatching elimination; robot navigation; dynamic environment; catadioptric panoramic image visual homing; mismatching elimination; robot navigation; dynamic environment; catadioptric panoramic image
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Zhu, Q.; Liu, C.; Cai, C. A Novel Robot Visual Homing Method Based on SIFT Features. Sensors 2015, 15, 26063-26084.

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