Detecting, locating and recognising human touches in social robots with contact microphones Articles uri icon

publication date

  • June 2020

start page

  • 1

end page

  • 16


  • 92(103670)

International Standard Serial Number (ISSN)

  • 0952-1976

Electronic International Standard Serial Number (EISSN)

  • 1873-6769


  • There are many situations in our daily life where touch gestures during natural human-human interaction take place: meeting people (shaking hands), personal relationships (caresses), moments of celebration or sadness (hugs), etc. Considering that robots are expected to form part of our daily life in the future, they should be endowed with the capacity of recognising these touch gestures and the part of its body that has been touched since the gesture's meaning may differ. Therefore, this work presents a learning system for both purposes: detect and recognise the type of touch gesture (stroke, tickle, tap and slap) and its localisation. The interpretation of the meaning of the gesture is out of the scope of this paper. Different technologies have been applied to perceive touch by a social robot, commonly using a large number of sensors. Instead, our approach uses 3 contact microphones installed inside some parts of the robot. The audio signals generated when the user touches the robot are sensed by the contact microphones and processed using Machine Learning techniques [...]


  • acoustic sensing; human-robot interaction; machine learning applications; social robots; touch gesture recognition; touch localisation