Textile Pressure Mapping Sensor for Emotional Touch Detection in Human-Robot Interaction

Bo Zhou, Carlos Andres Velez Altamirano, Heber Cruz Zurian, Seyed Reza Atefi, Erik Billing, Fernando Seoane Martinez, Paul Lukowicz

In: Sensors - Open Access Journal (Sensors) 17 11 Seite 2585 Multidisciplinary Digital Publishing Institute (MDPI) 2017.


In this paper, we developed a fully textile sensing fabric for tactile touch sensing as the robot skin to detect human-robot interactions. The sensor covers a 20-by-20 cm2 area with 400 sensitive points and samples at 50 Hz per point. We defined seven gestures which are inspired by the social and emotional interactions of typical people to people or pet scenarios. We conducted two groups of mutually blinded experiments, involving 29 participants in total. The data processing algorithm first reduces the spatial complexity to frame descriptors, and temporal features are calculated through basic statistical representations and wavelet analysis. Various classifiers are evaluated and the feature calculation algorithms are analyzed in details to determine each stage and segments’ contribution. The best performing feature-classifier combination can recognize the gestures with a 93.3% accuracy from a known group of participants, and 89.1% from strangers.

Weitere Links

Textile_Pressure_Mapping_Sensor_for_Emotional_Touch_Detection_in_Human-Robot_Interaction.pdf (pdf, 16 MB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence