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

Taher Abbas Shangari, Vida Shams, Bita Azari, Faraz Shamshirdar, Jacky Baltes, Soroush Sadeghnejad

研究成果: 雜誌貢獻期刊論文同行評審

4 引文 斯高帕斯(Scopus)

摘要

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.

原文英語
文章編號e8
期刊Knowledge Engineering Review
32
DOIs
出版狀態已發佈 - 2016 8月 4
對外發佈

ASJC Scopus subject areas

  • 軟體
  • 人工智慧

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