A System-Level Brain Model for Enactive Haptic Perception in a Humanoid Robot
Ingvarsdóttir, Kristín Ósk; Johansson, Birger; Tjøstheim, Trond A.; Balkenius, Christian (2023-09-22). A System-Level Brain Model for Enactive Haptic Perception in a Humanoid Robot Artificial Neural Networks and Machine Learning – ICANN 2023, 14254,, 432 - 443. The 32nd International Conference on Artificial Neural Networks (ICANN 2023): Springer
Conference Proceeding/Paper
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Published
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English
Authors:
Ingvarsdóttir, Kristín Ósk
;
Johansson, Birger
;
Tjøstheim, Trond A.
;
Balkenius, Christian
Department:
Cognitive Science
eSSENCE: The e-Science Collaboration
Cognitive modeling
LU Profile Area: Natural and Artificial Cognition
Research Group:
Cognitive modeling
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.
Keywords:
humanoid robot ;
Object categorization ;
haptic perception ;
Affordances ;
Enactive perception
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