A Novel Robot Visual Homing Method Based on SIFT Features

Sensors

Qidan Zhu²  Chuanjia Liu¹  Chengtao Cai² 

[1] College of Automation, Harbin Engineering University, Harbin 150001, China;

关键词: visual homing;    mismatching elimination;    robot navigation;    dynamic environment;    catadioptric panoramic image;   

DOI  :  10.3390/s151026063

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.