A System Design for Tactile Recognition of Human-Robot Contact State

Hiroyasu Iwata*, Shigeki Sugano

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

4 Citations (Scopus)


In this paper, we propose a method for designing an identification system of human-robot contact states based on tactile recognition. First, a method of quantifying tactile cognition of a human (receiver) touched by other people (toucher) using a neural network called MCP (Modified CounterPropagation ) is presented, which matches the verbal response by the receiver with tactile stimulation detected during physical interference and contact utilizing tactile interface. It is incorporated that the probability of corresponding contact state is determined, based on the degree of similarity of the characteristics between new input data and reference data patterns stored in advance. Referring to the SOM (Self-Organizing Maps) formed through learning, which contains the relationship between contact states and tactile stimulation detected, a robot that comes into contact with a human can recognize and infer contact states from tactile stimulation like the receiver. Next, in order to accomplish high-performance of contact state identification by improving the learning performance, an evaluation criterion to quantify the discriminatability of contact states is proposed. Finally, the experimental results confirm that the proposed method is useful for identifying contact states, based on only tactile sensing, as represented by the receiver.

Original languageEnglish
Number of pages6
Publication statusPublished - 2003 Dec 26
Event2003 IEEE/RSJ International Conference on Intelligent Robots and Systems - Las Vegas, NV, United States
Duration: 2003 Oct 272003 Oct 31


Conference2003 IEEE/RSJ International Conference on Intelligent Robots and Systems
Country/TerritoryUnited States
CityLas Vegas, NV


  • Artificial Tactile Cognition
  • Human Robot Interaction
  • Human Robot Tactile Interface
  • Humanoid Robot
  • Self-Organizing Maps

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications


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