Author

Bo Zhou, Heber Cruz Zurian, Seyed Reza Atefi, Erik Billing, Fernando Seoane, Paul Lukowicz

Abstract

In this paper, we developed a fully textile sensing fabric for tactile touch sensing as the robot skin to detect human- robot interactions. We defined seven gestures which are inspired by the interactions of typical people to people and pet scenarios. Through evaluation experiment with 5 participants, the machine learning algorithm can recognize the gesture with a 98% accuracy if the algorithm has encountered the person before, and 86.8% accuracy if the person is excluded in the training data.   [Download]

BibTex

@inproceedings {Zhou:TouchMe:2017:9497,
	number = {}, 
	month = {}, 
	year = {2017}, 
	title = {TouchMe : Full-textile Touch Sensitive Skin for Encouraging Human-Robot Interaction}, 
	journal = {}, 
	volume = {}, 
	pages = {}, 
	publisher = {IEEE}, 
	author = {Bo Zhou, Heber Cruz Zurian, Seyed Reza Atefi, Erik Billing, Fernando Seoane, Paul Lukowicz}, 
	keywords = {smart textile; textile pressure mapping matrix; robot skin; tactile sensing}
}