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.
Textile Pressure Mapping Sensor for Emotional Touch Detection in Human-Robot Interaction
Bo Zhou,Carlos Andres Velez Altamirano,H. Cruz,S. Atefi,E. Billing,F. Seoane,P. Lukowicz
Published 2017 in Italian National Conference on Sensors
ABSTRACT
PUBLICATION RECORD
- Publication year
2017
- Venue
Italian National Conference on Sensors
- Publication date
2017-11-01
- Fields of study
Medicine, Computer Science, Engineering
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
CITATION MAP
EXTRACTION MAP
CLAIMS
- No claims are published for this paper.
CONCEPTS
- No concepts are published for this paper.
REFERENCES
Showing 1-28 of 28 references · Page 1 of 1
CITED BY
Showing 1-24 of 24 citing papers · Page 1 of 1