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A Stimulus-Response Framework for Robot Control

A Stimulus-Response Framework for Robot Control A Stimulus-Response Framework for Robot Control MARIO GIANNI, ALCOR Laboratory, DIIAG, Sapienza, University of Rome, Italy GEERT-JAN M. KRUIJFF, Nuance Deutschland GmbH, Aachen, Germany FIORA PIRRI, ALCOR Laboratory, DIIAG, Sapienza, University of Rome, Italy We propose in this article a new approach to robot cognitive control based on a stimulus-response framework that models both a robot's stimuli and the robot's decision to switch tasks in response to or inhibit the stimuli. In an autonomous system, we expect a robot to be able to deal with the whole system of stimuli and to use them to regulate its behavior in real-world applications. The proposed framework contributes to the state of the art of robot planning and high-level control in that it provides a novel perspective on the interaction between robot and environment. Our approach is inspired by Gibson's constructive view of the concept of a stimulus and by the cognitive control paradigm of task switching. We model the robot's response to a stimulus in three stages. We start by defining the stimuli as perceptual functions yielded by the active robot processes and learned via an informed logistic regression. Then we model the stimulus-response relationship by estimating a score matrix http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Interactive Intelligent Systems (TiiS) Association for Computing Machinery

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2015 by ACM Inc.
ISSN
2160-6455
DOI
10.1145/2677198
Publisher site
See Article on Publisher Site

Abstract

A Stimulus-Response Framework for Robot Control MARIO GIANNI, ALCOR Laboratory, DIIAG, Sapienza, University of Rome, Italy GEERT-JAN M. KRUIJFF, Nuance Deutschland GmbH, Aachen, Germany FIORA PIRRI, ALCOR Laboratory, DIIAG, Sapienza, University of Rome, Italy We propose in this article a new approach to robot cognitive control based on a stimulus-response framework that models both a robot's stimuli and the robot's decision to switch tasks in response to or inhibit the stimuli. In an autonomous system, we expect a robot to be able to deal with the whole system of stimuli and to use them to regulate its behavior in real-world applications. The proposed framework contributes to the state of the art of robot planning and high-level control in that it provides a novel perspective on the interaction between robot and environment. Our approach is inspired by Gibson's constructive view of the concept of a stimulus and by the cognitive control paradigm of task switching. We model the robot's response to a stimulus in three stages. We start by defining the stimuli as perceptual functions yielded by the active robot processes and learned via an informed logistic regression. Then we model the stimulus-response relationship by estimating a score matrix

Journal

ACM Transactions on Interactive Intelligent Systems (TiiS)Association for Computing Machinery

Published: Jan 28, 2015

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