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Inter-humanoid robot interaction with emphasis on detection: a comparison study

Published online by Cambridge University Press:  02 February 2017

Taher Abbas Shangari
Affiliation:
Bio-Inspired System Design Lab, Amirkabir University of Technology (Tehran Polytechnic), No. 424, Hafez Avenue, PO Box 15875-4413, Tehran, Iran e-mail: abbasitaher@gmail.com; vidashams1991@gmail.com; bita.az94@gmail.com; faraz.shamshirdar@gmail.com; s.sadeghnejad@aut.ac.ir
Vida Shams
Affiliation:
Bio-Inspired System Design Lab, Amirkabir University of Technology (Tehran Polytechnic), No. 424, Hafez Avenue, PO Box 15875-4413, Tehran, Iran e-mail: abbasitaher@gmail.com; vidashams1991@gmail.com; bita.az94@gmail.com; faraz.shamshirdar@gmail.com; s.sadeghnejad@aut.ac.ir
Bita Azari
Affiliation:
Bio-Inspired System Design Lab, Amirkabir University of Technology (Tehran Polytechnic), No. 424, Hafez Avenue, PO Box 15875-4413, Tehran, Iran e-mail: abbasitaher@gmail.com; vidashams1991@gmail.com; bita.az94@gmail.com; faraz.shamshirdar@gmail.com; s.sadeghnejad@aut.ac.ir
Faraz Shamshirdar
Affiliation:
Bio-Inspired System Design Lab, Amirkabir University of Technology (Tehran Polytechnic), No. 424, Hafez Avenue, PO Box 15875-4413, Tehran, Iran e-mail: abbasitaher@gmail.com; vidashams1991@gmail.com; bita.az94@gmail.com; faraz.shamshirdar@gmail.com; s.sadeghnejad@aut.ac.ir
Jacky Baltes
Affiliation:
Autonomous Agents Laboratory, University of Manitoba, Winnipeg, Canada, R3T 2N2 e-mail: jacky@cs.umanitoba.ca
Soroush Sadeghnejad
Affiliation:
Bio-Inspired System Design Lab, Amirkabir University of Technology (Tehran Polytechnic), No. 424, Hafez Avenue, PO Box 15875-4413, Tehran, Iran e-mail: abbasitaher@gmail.com; vidashams1991@gmail.com; bita.az94@gmail.com; faraz.shamshirdar@gmail.com; s.sadeghnejad@aut.ac.ir

Abstract

Robot Interaction has always been a challenge in collaborative robotics. In tasks comprising Inter-Robot Interaction, robot detection is very often needed. We explore humanoid robots detection because, humanoid robots can be useful in many scenarios, and everything from helping elderly people live in their own homes to responding to disasters. Cameras are chosen because they are reach and cheap sensors, and there are lots of mature two-dimensional (2D) and 3D computer vision libraries which facilitate Image analysis. To tackle humanoid robot detection effectively, we collected a data set of various humanoid robots with different sizes in different environments. Afterward, we tested the well-known cascade classifier in combination with several image descriptors like Histograms of Oriented Gradients (HOG), Local Binary Patterns (LBP), etc. on this data set. Among the feature sets, Haar-like has the highest accuracy, LBP the highest recall, and HOG the highest precision. Considering Inter-Robot Interaction, it is evident that false positives are less troublesome than false negatives, thus LBP is more useful than the others.

Type
Review Article
Copyright
© Cambridge University Press, 2017 

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Footnotes

These authors contributed equally to this work.

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