Control System Design for Smart Wheelchair Robot

Anshar, M; Sadjad, R; Dewiani,; Abry, M; Prayudha, R; Fiqhi,; Takbir, M

Control System Design for Smart Wheelchair Robot

Anshar, M

Sadjad, R Dewiani, Abry, M Prayudha, R Fiqhi, Takbir, M

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Publisher:: AIP Publishing
Publication Type:: Conference Proceeding
Citation:: AIP Conference Proceedings, 2022, 2543, (1), pp. 040005
Issue Date:: 2022-11-16

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Field	Value	Language
dc.contributor.author	Anshar, M https://orcid.org/0000-0002-6477-5257
dc.contributor.author	Sadjad, R
dc.contributor.author	Dewiani,
dc.contributor.author	Abry, M
dc.contributor.author	Prayudha, R
dc.contributor.author	Fiqhi,
dc.contributor.author	Takbir, M
dc.date.accessioned	2023-04-20T04:20:41Z
dc.date.available	2023-04-20T04:20:41Z
dc.date.issued	2022-11-16
dc.identifier.citation	AIP Conference Proceedings, 2022, 2543, (1), pp. 040005
dc.identifier.isbn	9780735443587
dc.identifier.issn	0094-243X
dc.identifier.issn	1551-7616
dc.identifier.uri	http://hdl.handle.net/10453/170031
dc.description.abstract	Over 1 billion people or approximately 15% of the world population that have disabilities levels and lesser access to health facilities. The majority of this population with physical disabilities, i.e. around 80%, is from low-income countries; and it is estimated only 5% up to 15% in developing countries, including Indonesia, that have access to assistive device technologies. Indonesia, for instance, has 20% of the total 240 million people who have disabilities in daily and social activities, and about 10% or 4.8 million people require wheelchair due to inability to walk. One major factor affecting limited access to this technology is poverty level. Besides, the ones available on the market are manually controlled by joysticks which are not user-friendly especially diffable with motoric problems. This paper highlights the control system design for a smart wheelchair prototype and the smart interface utilising voice-based and vision-based mechanism, namely voice and image guided direction. The results show that during image guided direction scenario, the system functions accurately with the intensity of light 0.4 to 400 lux without direct sun light, whilst voice guided direction functions effectively regardless any light source disturbances. However, there are some delays between 1.11 to 3.66 seconds for commands to activate the sensor while commands for actuating the motors will generate a delay of 2.19 to 4.62 seconds. Some discrepancies occur during motions, trajectory deviates in X ordinate direction, 83° in forward motion, 63° in reverse motion, 39° in left and 51° in right. These situations could be compensated by implementing feedback control as the current one is only an open-loop control.
dc.language	en
dc.publisher	AIP Publishing
dc.relation.ispartof	AIP Conference Proceedings
dc.relation.ispartof	THE PROCEEDINGS OF THE 4TH EPI INTERNATIONAL CONFERENCE ON SCIENCE AND ENGINEERING (EICSE) 2020
dc.relation.isbasedon	10.1063/5.0095676
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Control System Design for Smart Wheelchair Robot
dc.type	Conference Proceeding
utslib.citation.volume	2543
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2023-04-20T04:20:40Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	2543
utslib.citation.issue	1

Abstract:

Over 1 billion people or approximately 15% of the world population that have disabilities levels and lesser access to health facilities. The majority of this population with physical disabilities, i.e. around 80%, is from low-income countries; and it is estimated only 5% up to 15% in developing countries, including Indonesia, that have access to assistive device technologies. Indonesia, for instance, has 20% of the total 240 million people who have disabilities in daily and social activities, and about 10% or 4.8 million people require wheelchair due to inability to walk. One major factor affecting limited access to this technology is poverty level. Besides, the ones available on the market are manually controlled by joysticks which are not user-friendly especially diffable with motoric problems. This paper highlights the control system design for a smart wheelchair prototype and the smart interface utilising voice-based and vision-based mechanism, namely voice and image guided direction. The results show that during image guided direction scenario, the system functions accurately with the intensity of light 0.4 to 400 lux without direct sun light, whilst voice guided direction functions effectively regardless any light source disturbances. However, there are some delays between 1.11 to 3.66 seconds for commands to activate the sensor while commands for actuating the motors will generate a delay of 2.19 to 4.62 seconds. Some discrepancies occur during motions, trajectory deviates in X ordinate direction, 83° in forward motion, 63° in reverse motion, 39° in left and 51° in right. These situations could be compensated by implementing feedback control as the current one is only an open-loop control.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/170031