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Relative Localization for Mobile Robot using 3D Reconstruction of Scale-Invariant Features  

Kil, Se-Kee (인하대학교 전자공학과)
Lee, Jong-Shill (한양대학교 의공학교실)
Ryu, Je-Goon (한국산업기술대학교 전자공학과)
Lee, Eung-Hyuk (한국산업기술대학교 전자공학과)
Hong, Seung-Hong (인하대학교 전자공학과)
Shen, Dong-Fan (인하대학교 전자공학과)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers D / v.55, no.4, 2006 , pp. 173-180 More about this Journal
Abstract
A key component of autonomous navigation of intelligent home robot is localization and map building with recognized features from the environment. To validate this, accurate measurement of relative location between robot and features is essential. In this paper, we proposed relative localization algorithm based on 3D reconstruction of scale invariant features of two images which are captured from two parallel cameras. We captured two images from parallel cameras which are attached in front of robot and detect scale invariant features in each image using SIFT(scale invariant feature transform). Then, we performed matching for the two image's feature points and got the relative location using 3D reconstruction for the matched points. Stereo camera needs high precision of two camera's extrinsic and matching pixels in two camera image. Because we used two cameras which are different from stereo camera and scale invariant feature point and it's easy to setup the extrinsic parameter. Furthermore, 3D reconstruction does not need any other sensor. And the results can be simultaneously used by obstacle avoidance, map building and localization. We set 20cm the distance between two camera and capture the 3frames per second. The experimental results show :t6cm maximum error in the range of less than 2m and ${\pm}15cm$ maximum error in the range of between 2m and 4m.
Keywords
Obstacle Detection; Localization; Relative Location; SIFT; 3D Reconstruction;
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