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Sensors 2016, 16(8), 1180; doi:10.3390/s16081180

Object Detection Applied to Indoor Environments for Mobile Robot Navigation

Department of Systems Engineering and Automation, Carlos III University of Madrid, Madrid 28911, Spain
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Author to whom correspondence should be addressed.
Academic Editor: Gabriel Oliver-Codina
Received: 6 April 2016 / Revised: 28 June 2016 / Accepted: 20 July 2016 / Published: 28 July 2016
(This article belongs to the Section Physical Sensors)

Abstract

To move around the environment, human beings depend on sight more than their other senses, because it provides information about the size, shape, color and position of an object. The increasing interest in building autonomous mobile systems makes the detection and recognition of objects in indoor environments a very important and challenging task. In this work, a vision system to detect objects considering usual human environments, able to work on a real mobile robot, is developed. In the proposed system, the classification method used is Support Vector Machine (SVM) and as input to this system, RGB and depth images are used. Different segmentation techniques have been applied to each kind of object. Similarly, two alternatives to extract features of the objects are explored, based on geometric shape descriptors and bag of words. The experimental results have demonstrated the usefulness of the system for the detection and location of the objects in indoor environments. Furthermore, through the comparison of two proposed methods for extracting features, it has been determined which alternative offers better performance. The final results have been obtained taking into account the proposed problem and that the environment has not been changed, that is to say, the environment has not been altered to perform the tests. View Full-Text
Keywords: object detection; object classification; shapes descriptors; Support Vector Machine; mobile robots; robot navigation object detection; object classification; shapes descriptors; Support Vector Machine; mobile robots; robot navigation
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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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MDPI and ACS Style

Hernández, A.C.; Gómez, C.; Crespo, J.; Barber, R. Object Detection Applied to Indoor Environments for Mobile Robot Navigation. Sensors 2016, 16, 1180.

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