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Associating SOM Representations of Haptic Submodalities

Författare

Redaktör

  • Subramanian Ramamoorthy
  • Gillian M. Hayes

Summary, in English

We have experimented with a bio-inspired selforganizing
texture and hardness perception system which
automatically learns to associate the representations of the two
submodalities with each other. To this end we have developed
a microphone based texture sensor and a hardness sensor that measures the compression of the material at a constant pressure. The system is based on a novel variant of the Self-Organizing Map (SOM), called Associative Self-Organizing Map (A-SOM). The A-SOM both develops a representation of its input space and learns to associate this with the activity in an external SOM or A-SOM. The system was trained and tested with multiple samples gained from the exploration of a set of 4 soft and 4 hard objects of different materials with varying textural properties. The system successfully found representations of the texture and hardness submodalities and also learned to associate these with each other.

Publiceringsår

2008

Språk

Engelska

Sidor

124-129

Publikation/Tidskrift/Serie

Proceedings of Towards Autonomous Robotic Systems 2008 : The University of Edinburgh. September 1 st – 3 rd 2008

Dokumenttyp

Konferensbidrag

Förlag

University of Edinburgh

Ämne

  • Computer Vision and Robotics (Autonomous Systems)

Conference name

Towards Autonomous Robotic Systems 2008

Conference date

2008-09-01 - 2008-09-03

Conference place

Edinburgh, United Kingdom

Status

Published

Projekt

  • Ikaros: An infrastructure for system level modelling of the brain

Forskningsgrupp

  • Lund University Cognitive Science (LUCS)

ISBN/ISSN/Övrigt

  • ISBN: 1906849005
  • ISBN: 9781906849009