A Modular Dynamic Sensorimotor Model for Affordances Learning, Sequences Planning, and Tool-Use

This paper proposes a computational model for learning robot control and sequence planning based on the ideomotor principle. This model encodes covariation laws between sensors and motors in a modular fashion and exploits these primitive skills to build complex action sequences, potentially involvin...

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Bibliographic Details
Published in:IEEE transactions on cognitive and developmental systems 2018-03, Vol.10 (1), p.72-87
Main Authors: Braud, Raphael, Pitti, Alexandre, Gaussier, Philippe
Format: Article
Language:English
Subjects:
Affordance
Artificial Intelligence
Cognitive science
Computational modeling
Computer Science
Computer Vision and Pattern Recognition
Embedded Systems
Encoding
Human-Computer Interaction
ideomotor principle
Image Processing
Learning
Machine Learning
Modeling and Simulation
Modular systems
Neural and Evolutionary Computing
Neuroscience
Object recognition
Planning
Psychology
Robot arms
Robot control
Robot kinematics
Robot sensing systems
Robotics
sensorimotor laws
sequences
tool-use
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Summary:This paper proposes a computational model for learning robot control and sequence planning based on the ideomotor principle. This model encodes covariation laws between sensors and motors in a modular fashion and exploits these primitive skills to build complex action sequences, potentially involving tool-use. Implemented for a robotic arm, the model starts with raw unlabeled sensor and motor vectors and autonomously assigns functions to neutral objects in the environment. Our experimental evaluation highlights the emergent properties of such a modular system and we discuss their consequences from ideomotor and sensorimotor-theoretic perspectives.
ISSN:2379-8920
2379-8939
DOI:10.1109/TCDS.2016.2647439