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A System-Level Brain Model for Enactive Haptic Perception in a Humanoid Robot

Ingvarsdóttir, Kristín Ósk LU ; Johansson, Birger LU orcid ; Tjøstheim, Trond A. LU and Balkenius, Christian LU orcid (2023) The 32nd International Conference on Artificial Neural Networks (ICANN 2023) In Lecture Notes in Computer Science 14254. p.432-443
Abstract
Perception is not a passive process but the result of an interaction between an organism and the environment. This is especially clear in haptic perception that depends entirely on tactile exploration of an object. We investigate this idea in a system-level brain model of somatosensory and motor cortex and show how it can use signals from a humanoid robot to categorize different object. The model suggests a number of critical properties that the sensorimotor system must have to support this form of enactive perception. Furthermore, we show that motor feedback during controlled movements is sufficient for haptic object categorization.
Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
humanoid robot, Object categorization, haptic perception, Affordances, Enactive perception
host publication
Artificial Neural Networks and Machine Learning – ICANN 2023
series title
Lecture Notes in Computer Science
volume
14254
pages
11 pages
publisher
Springer
conference name
The 32nd International Conference on Artificial Neural Networks (ICANN 2023)
conference dates
2023-09-26 - 2023-09-29
external identifiers
  • scopus:85174611782
ISSN
1611-3349
0302-9743
ISBN
978-3-031-44206-3
978-3-031-44207-0
DOI
10.1007/978-3-031-44207-0_36
language
English
LU publication?
yes
id
0b72809b-2093-43d1-a6b4-2a18751387b7
date added to LUP
2023-09-24 12:04:06
date last changed
2024-04-24 19:25:22
@inproceedings{0b72809b-2093-43d1-a6b4-2a18751387b7,
  abstract     = {{Perception is not a passive process but the result of an interaction between an organism and the environment. This is especially clear in haptic perception that depends entirely on tactile exploration of an object. We investigate this idea in a system-level brain model of somatosensory and motor cortex and show how it can use signals from a humanoid robot to categorize different object. The model suggests a number of critical properties that the sensorimotor system must have to support this form of enactive perception. Furthermore, we show that motor feedback during controlled movements is sufficient for haptic object categorization.}},
  author       = {{Ingvarsdóttir, Kristín Ósk and Johansson, Birger and Tjøstheim, Trond A. and Balkenius, Christian}},
  booktitle    = {{Artificial Neural Networks and Machine Learning – ICANN 2023}},
  isbn         = {{978-3-031-44206-3}},
  issn         = {{1611-3349}},
  keywords     = {{humanoid robot; Object categorization; haptic perception; Affordances; Enactive perception}},
  language     = {{eng}},
  month        = {{09}},
  pages        = {{432--443}},
  publisher    = {{Springer}},
  series       = {{Lecture Notes in Computer Science}},
  title        = {{A System-Level Brain Model for Enactive Haptic Perception in a Humanoid Robot}},
  url          = {{http://dx.doi.org/10.1007/978-3-031-44207-0_36}},
  doi          = {{10.1007/978-3-031-44207-0_36}},
  volume       = {{14254}},
  year         = {{2023}},
}