A Survey on Perception Methods for Human–Robot Int

Authors: Haibin Yan Marcelo H Ang Aun Neow Poo

Publish Date: 2013/07/04

Volume: 6, Issue: 1, Pages: 85-119

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Abstract

For human–robot interaction HRI perception is one of the most important capabilities This paper reviews several widely used perception methods of HRI in social robots Specifically we investigate general perception tasks crucial for HRI such as where the objects are located in the rooms what objects are in the scene and how they interact with humans We first enumerate representative social robots and summarize the most three important perception methods from these robots feature extraction dimensionality reduction and semantic understanding For feature extraction four widely used signals including visualbased audiobased tactilebased and rang sensorsbased are reviewed and they are compared based on their advantages and disadvantages For dimensionality reduction representative methods including principle component analysis PCA linear discriminant analysis LDA and locality preserving projections LPP are reviewed For semantic understanding conventional techniques for several typical applications such as object recognition object tracking object segmentation and speaker localization are discussed and their characteristics and limitations are also analyzed Moreover several popular data sets used in social robotics and published semantic understanding results are analyzed and compared in light of our analysis of HRI perception methods Lastly we suggest important future work to analyze fundamental questions on perception methods in HRI

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