Confirmation of gripping surface status classification using HMM and tactile sensor array

DOI Web Site 4 References

Bibliographic Information

Other Title
  • 触覚センサアレイを用いたHMMによる把持面状態の識別手法(感性情報処理とマルチメディア技術および一般)
  • 触覚センサアレイを用いたHMMによる把持面状態の識別手法
  • ショッカク センサアレイ オ モチイタ HMM ニ ヨル ハジメン ジョウタイ ノ シキベツ シュホウ

Search this article

Abstract

We have designed and fabricated a tactile sensors array with three inclined micro-cantilevers on a single sensor embedded in elastomer. Each sensor element can detect both normal and shear stresses. In this paper, we propose classification method of gripping status using sensor array and machine learning algorithm based on hidden marcov model. By integrating multiple sensor data using machine learning algorithm using hidden marcov model, our method allows to detect partial contact status such as non-contact, three types of partial contact, full-contact. Through experiments, we confirmed that our method achieves better classification ratio than existing methods using single sensor data.

Journal

  • ITE Technical Report

    ITE Technical Report 34.18 (0), 39-42, 2010

    The Institute of Image Information and Television Engineers

References(4)*help

See more

Keywords

Details 詳細情報について

Report a problem

Back to top