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A Fabric-Based Sensing System for Recognizing Social Touch




We present a fabric-based piezoresistive tactile sensor system designed to detect social touch gestures on a robot. The unique sensor design utilizes three layers of low-conductivity fabric sewn together on alternating edges to form an accordion pattern and secured between two outer high-conductivity layers. This five-layer design demonstrates a greater resistance range and better low-force sensitivity than previous designs that use one layer of low-conductivity fabric with or without a plastic mesh layer. An individual sensor from our system can presently identify six different communication gestures – squeezing, patting, scratching, poking, hand resting without movement, and no touch – with an average accuracy of 90%. A layer of foam can be added beneath the sensor to make a rigid robot more appealing for humans to touch without inhibiting the system’s ability to register social touch gestures.

Author(s): Rachael Bevill Burns and Hyosang Lee and Hasti Seifi and Katherine J. Kuchenbecker
Year: 2020
Month: March

Department(s): Haptic Intelligence
Research Project(s): Haptic Empathetic Robot Animal (HERA)
Bibtex Type: Miscellaneous (misc)

Address: Washington, DC, USA
How Published: Work-in-progress paper (3 pages) presented at the IEEE Haptics Symposium
State: Published


  title = {A Fabric-Based Sensing System for Recognizing Social Touch},
  author = {Burns, Rachael Bevill and Lee, Hyosang and Seifi, Hasti and Kuchenbecker, Katherine J.},
  howpublished = {Work-in-progress paper (3 pages) presented at the IEEE Haptics Symposium},
  address = {Washington, DC, USA},
  month = mar,
  year = {2020},
  month_numeric = {3}