Loose fruit collection using a delta robot

With the increase of the global demand for palm oil, mechanizing oil palm plantations is becoming more and more significant. Even after almost a century since the first oil palm plantation in Malaysia, these plantations still rely almost-completely on manual labour for many of the harvesting and col...

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Main Author:	Abdeltawab, Amr. Ahmed Abdelsattar
Format:	Thesis
Language:	English
Published:	2022
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/99367/1/AmrAhmedAbdelsattarMSKE2022.pdf
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id	my-utm-ep.99367
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spelling	my-utm-ep.993672023-02-23T04:02:21Z Loose fruit collection using a delta robot 2022 Abdeltawab, Amr. Ahmed Abdelsattar TK Electrical engineering. Electronics Nuclear engineering With the increase of the global demand for palm oil, mechanizing oil palm plantations is becoming more and more significant. Even after almost a century since the first oil palm plantation in Malaysia, these plantations still rely almost-completely on manual labour for many of the harvesting and collection of the fresh fruit bunch (FFB) and the loose fruit (LF). Loose fruits that fall away from the FFB have the highest oil content since they are originally from the outer layer of the bunch. Due to its economic value, collectors have to manually collect these fruits which can result in many musculoskeletal disorders due to the bad back, hip and knee postures they have to endure on daily basis. Increasing the productivity and minimizing these issues of LF collection can be achieved by developing machines that can carry out the collection process seamlessly. Although many mechanisms like vacuum type collecting as well as racking tools have been implemented, each of which comes with constraints and issues like debris filtering and intensive manual labour. With the evolvement of robotics as well as machine vision and their applications in recent years, robotic collection of these fruits became more and more viable. In this work, automatic collection of these fruits using a delta robot along with a vision system for detection and localization is explored. A proof of concept of the collection process using a parallel delta link robot under a controlled environment is simulated. Additionally, a more versatile YOLO based LF detection system is explored. Although the robot displayed a capability of collecting over 50 LFs per minute, the integrated vision system for the delta robot proved incompetent when presented with different variations of LF and hence, a separate YOLO-based LF detection system is introduced. 2022 Thesis http://eprints.utm.my/id/eprint/99367/ http://eprints.utm.my/id/eprint/99367/1/AmrAhmedAbdelsattarMSKE2022.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:149985 masters Universiti Teknologi Malaysia, Faculty of Engineering - School of Electrical Engineering Faculty of Engineering - School of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Abdeltawab, Amr. Ahmed Abdelsattar Loose fruit collection using a delta robot
description	With the increase of the global demand for palm oil, mechanizing oil palm plantations is becoming more and more significant. Even after almost a century since the first oil palm plantation in Malaysia, these plantations still rely almost-completely on manual labour for many of the harvesting and collection of the fresh fruit bunch (FFB) and the loose fruit (LF). Loose fruits that fall away from the FFB have the highest oil content since they are originally from the outer layer of the bunch. Due to its economic value, collectors have to manually collect these fruits which can result in many musculoskeletal disorders due to the bad back, hip and knee postures they have to endure on daily basis. Increasing the productivity and minimizing these issues of LF collection can be achieved by developing machines that can carry out the collection process seamlessly. Although many mechanisms like vacuum type collecting as well as racking tools have been implemented, each of which comes with constraints and issues like debris filtering and intensive manual labour. With the evolvement of robotics as well as machine vision and their applications in recent years, robotic collection of these fruits became more and more viable. In this work, automatic collection of these fruits using a delta robot along with a vision system for detection and localization is explored. A proof of concept of the collection process using a parallel delta link robot under a controlled environment is simulated. Additionally, a more versatile YOLO based LF detection system is explored. Although the robot displayed a capability of collecting over 50 LFs per minute, the integrated vision system for the delta robot proved incompetent when presented with different variations of LF and hence, a separate YOLO-based LF detection system is introduced.
format	Thesis
qualification_level	Master's degree
author	Abdeltawab, Amr. Ahmed Abdelsattar
author_facet	Abdeltawab, Amr. Ahmed Abdelsattar
author_sort	Abdeltawab, Amr. Ahmed Abdelsattar
title	Loose fruit collection using a delta robot
title_short	Loose fruit collection using a delta robot
title_full	Loose fruit collection using a delta robot
title_fullStr	Loose fruit collection using a delta robot
title_full_unstemmed	Loose fruit collection using a delta robot
title_sort	loose fruit collection using a delta robot
granting_institution	Universiti Teknologi Malaysia, Faculty of Engineering - School of Electrical Engineering
granting_department	Faculty of Engineering - School of Electrical Engineering
publishDate	2022
url	http://eprints.utm.my/id/eprint/99367/1/AmrAhmedAbdelsattarMSKE2022.pdf
_version_	1776100593177198592

Loose fruit collection using a delta robot

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