Tongue-Based Electrotactile Feedback to Perceive Objects Grasped by a Robotic Manipulator: Preliminary Results

Abstract

A sensate robotic gripper was developed and interfaced to an electrotactile tongue stimulation system. The prototype system permits grasped object recognition by the user without visual sensory input. Modifications of an existing two finger robotic gripper included the addition of six conductive polymer force sensors mounted in a pentagonal (24mm diameter) pattern with the sixth sensor placed in the center. Shape information from the robot gripper in contact with a test object is relayed to the user via patterned electrotactile stimulation on a micro-fabricated flexible tongue array. A previously developed Tongue Display Unit (TDU) provides the electrotactile stimulation, which pattern maps information from the six sensors to discrete groupings of electrodes on the 12 x 12 matrix tongue array. Modification of an existing software program facilitated a tongue mapping closely resembling the spatial layout of the six force sensors, A preliminary human subject study was performed to demonstrate the accuracy of recognition when presented with one of four basic shapes. Results indicate sensor resolution and orientation influence performance, but even a limited configuration provides highly accurate shape recognition.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA410438

Entities

People

  • David K. Hall
  • Mitchell E. Tyler
  • Nicholas J. Droessler
  • Nicola J. Ferrier

Organizations

  • University of Wisconsin–Madison

Tags

Communities of Interest

  • Autonomy
  • Biomedical

DTIC Thesaurus Topics

  • Biomedical Engineering
  • Closed Loop Systems
  • Computer Vision
  • Computers
  • Control
  • Control Knobs
  • Control Systems
  • Engineering
  • Feedback
  • Graphical User Interface
  • Haptics
  • Human Factors Engineering
  • Human Systems Integration
  • Object Recognition
  • Prostheses And Implants
  • Recognition
  • User Interface

Readers

  • Nanofabrication and Microfabrication.
  • Robotics and Automation.
  • Speech Processing/Speech Recognition.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy