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Inter-humanoid robot interaction with emphasis on detection: acomparison 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 taskscomprising Inter-Robot Interaction, robot detection is very often needed. Weexplore humanoid robots detection because, humanoid robots can be useful in manyscenarios, and everything from helping elderly people live in their own homes toresponding to disasters. Cameras are chosen because they are reach and cheapsensors, and there are lots of mature two-dimensional (2D) and 3D computervision libraries which facilitate Image analysis. To tackle humanoid robotdetection effectively, we collected a data set of various humanoid robots withdifferent sizes in different environments. Afterward, we tested the well-knowncascade classifier in combination with several image descriptors like Histogramsof Oriented Gradients (HOG), Local Binary Patterns (LBP), etc. on this data set.Among the feature sets, Haar-like has the highest accuracy, LBP the highestrecall, and HOG the highest precision. Considering Inter-Robot Interaction, itis evident that false positives are less troublesome than false negatives, thusLBP is more useful than the others.

Information

Type
Review Article
Copyright
© Cambridge University Press, 2017 

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