Affective-model based high level controller for human-robot applications

The paper presents a real-time affective state detection namely the engagement level detection by using fuzzy classifier that can be applied to human-robot interaction. In order to develop the fuzzy classifier, the engagement model is developed using the data collected from a controlled design exper...

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Main Authors:	Sidek, Shahrul Na'im, Ismail, Elliana, Jalaludin, Nor Anija
Format:	Article
Language:	English
Published:	Elsevier 2012
Subjects:	TA168 Systems engineering
Online Access:	http://irep.iium.edu.my/24508/ http://irep.iium.edu.my/24508/ http://irep.iium.edu.my/24508/ http://irep.iium.edu.my/24508/1/Affective-Model_Based_High-Level.pdf

id	iium-24508
recordtype	eprints
spelling	iium-245082012-11-06T07:27:15Z http://irep.iium.edu.my/24508/ Affective-model based high level controller for human-robot applications Sidek, Shahrul Na'im Ismail, Elliana Jalaludin, Nor Anija TA168 Systems engineering The paper presents a real-time affective state detection namely the engagement level detection by using fuzzy classifier that can be applied to human-robot interaction. In order to develop the fuzzy classifier, the engagement model is developed using the data collected from a controlled design experiment. In the experiment, the data collected are from the total number of endogenous eye blinks and the total error from the trajectory the subjects have to follow in completing specific tasks. For the tasks, the subjects are asked to track a set of prescribed paths within the allocated times and have to obey different speed constraint. Various shapes of trajectories are given to the subjects in order to study the level of engagement while performing the task. The data then are used to develop the fuzzy classifier to measure the level of engagement (LOE) of the subjects. Following the experiments, a series of questionnaires are given to the subjects to validate the engagement model developed. The result from the fuzzy classifier is applied on a robotic model that has linear motion featured control. The LOE can be used to adapt the speed of the robotic platform model which is useful for the human-robot interaction In this paper, the engagement model is in the form of fuzzy classifier is designed as a higher level controller using Discrete Event system (DES) approach to control the speed of the robotic platform. Preliminary analysis on the high-level controller shows a promising result for future research in application for robot-assisted rehabilitation. Elsevier 2012 Article PeerReviewed application/pdf en http://irep.iium.edu.my/24508/1/Affective-Model_Based_High-Level.pdf Sidek, Shahrul Na'im and Ismail, Elliana and Jalaludin, Nor Anija (2012) Affective-model based high level controller for human-robot applications. Procedia Engineering, 41. pp. 812-818. ISSN 1877-7058 http://www.sciencedirect.com/science/article/pii/S1877705812026483# 10.1016/j.proeng.2012.07.248
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	TA168 Systems engineering
spellingShingle	TA168 Systems engineering Sidek, Shahrul Na'im Ismail, Elliana Jalaludin, Nor Anija Affective-model based high level controller for human-robot applications
description	The paper presents a real-time affective state detection namely the engagement level detection by using fuzzy classifier that can be applied to human-robot interaction. In order to develop the fuzzy classifier, the engagement model is developed using the data collected from a controlled design experiment. In the experiment, the data collected are from the total number of endogenous eye blinks and the total error from the trajectory the subjects have to follow in completing specific tasks. For the tasks, the subjects are asked to track a set of prescribed paths within the allocated times and have to obey different speed constraint. Various shapes of trajectories are given to the subjects in order to study the level of engagement while performing the task. The data then are used to develop the fuzzy classifier to measure the level of engagement (LOE) of the subjects. Following the experiments, a series of questionnaires are given to the subjects to validate the engagement model developed. The result from the fuzzy classifier is applied on a robotic model that has linear motion featured control. The LOE can be used to adapt the speed of the robotic platform model which is useful for the human-robot interaction In this paper, the engagement model is in the form of fuzzy classifier is designed as a higher level controller using Discrete Event system (DES) approach to control the speed of the robotic platform. Preliminary analysis on the high-level controller shows a promising result for future research in application for robot-assisted rehabilitation.
format	Article
author	Sidek, Shahrul Na'im Ismail, Elliana Jalaludin, Nor Anija
author_facet	Sidek, Shahrul Na'im Ismail, Elliana Jalaludin, Nor Anija
author_sort	Sidek, Shahrul Na'im
title	Affective-model based high level controller for human-robot applications
title_short	Affective-model based high level controller for human-robot applications
title_full	Affective-model based high level controller for human-robot applications
title_fullStr	Affective-model based high level controller for human-robot applications
title_full_unstemmed	Affective-model based high level controller for human-robot applications
title_sort	affective-model based high level controller for human-robot applications
publisher	Elsevier
publishDate	2012
url	http://irep.iium.edu.my/24508/ http://irep.iium.edu.my/24508/ http://irep.iium.edu.my/24508/ http://irep.iium.edu.my/24508/1/Affective-Model_Based_High-Level.pdf
first_indexed	2023-09-18T20:36:45Z
last_indexed	2023-09-18T20:36:45Z
_version_	1777409096514797568

Affective-model based high level controller for human-robot applications

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