國立虎尾科技大學 |

Machine vision system for robotic apple harvesting in fruiting wall orchards.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Machine vision system for robotic apple harvesting in fruiting wall orchards./
作者:	Silwal, Abhisesh.
面頁冊數:	1 online resource (152 pages)
附註:	Source: Dissertation Abstracts International, Volume: 78-08(E), Section: B.
Contained By:	Dissertation Abstracts International78-08B(E).
標題:	Robotics. -
電子資源:	click for full text (PQDT)
ISBN:	9781369618891

Machine vision system for robotic apple harvesting in fruiting wall orchards.
Silwal, Abhisesh.

Machine vision system for robotic apple harvesting in fruiting wall orchards. - 1 online resource (152 pages)

Source: Dissertation Abstracts International, Volume: 78-08(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

Mechanization in agriculture is often regarded as one of the greatest human achievements in the twentieth century. These technological advancements have led to significant reduction in human effort in the production of bulk agricultural commodities such as corn and wheat. Specialty crop industry such as fresh fruit market, on the other hand, are still dependent upon manual labor for various production operations such as training, pruning, and harvesting. Among these, tree fruit harvesting of high value crops like apples is the most labor intensive and time sensitive task that requires the right number of farm workers at right time. To increase productivity and reduce dependency on seasonal labor, researchers have proposed automated harvesting systems. Because of highly unstructured orchard environment and variable outdoor conditions, these technologies have achieved only limited successes in the past. No commercial viability has been achieved and every apple destined for fresh market is still handpicked. The lack of mechanized harvesting system has the potential to threaten the long-term sustainability of fresh fruit industry in the United States and around the world.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369618891Subjects--Topical Terms:

561941
Robotics.
Index Terms--Genre/Form:

554714
Electronic books.

Machine vision system for robotic apple harvesting in fruiting wall orchards.
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100 1 $a Silwal, Abhisesh. $3 1182137
245 1 0 $a Machine vision system for robotic apple harvesting in fruiting wall orchards.
264 0 $c 2016
300 $a 1 online resource (152 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 78-08(E), Section: B.
500 $a Adviser: Manoj Karkee.
502 $a Thesis (Ph.D.) $c Washington State University $d 2016.
504 $a Includes bibliographical references
520 $a Mechanization in agriculture is often regarded as one of the greatest human achievements in the twentieth century. These technological advancements have led to significant reduction in human effort in the production of bulk agricultural commodities such as corn and wheat. Specialty crop industry such as fresh fruit market, on the other hand, are still dependent upon manual labor for various production operations such as training, pruning, and harvesting. Among these, tree fruit harvesting of high value crops like apples is the most labor intensive and time sensitive task that requires the right number of farm workers at right time. To increase productivity and reduce dependency on seasonal labor, researchers have proposed automated harvesting systems. Because of highly unstructured orchard environment and variable outdoor conditions, these technologies have achieved only limited successes in the past. No commercial viability has been achieved and every apple destined for fresh market is still handpicked. The lack of mechanized harvesting system has the potential to threaten the long-term sustainability of fresh fruit industry in the United States and around the world.
520 $a This dissertation focuses on the study and evaluation of a machine vision and an integrated robotic system for automated harvesting of apples grown in modern fruiting wall orchards. The machine vision algorithm designed to work in orchard environment accurately detected apples growing individually as well as in heavy clusters under variable natural lighting conditions. A pragmatic approach to harvesting (also called hierarchical approach) showed that 98% of the fruit could be detected with iterative imaging and harvesting of most visible fruits. The integrated robotic system with global camera and custom built seven degrees of freedom manipulator successfully picked 84% of attempted fruit with 6 seconds of average harvest time per fruit. This approach of selective apple harvesting with a global camera system and low-cost manipulator show a huge potential for cost-effective robotic solutions for harvesting fresh market apples. However, several limitations still remain to be addressed for commercialization.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Robotics. $3 561941
650 4 $a Agricultural engineering. $3 1148660
655 7 $a Electronic books. $2 local $3 554714
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710 2 $a Washington State University. $b Biological and Agricultural Engineering. $3 1182138
773 0 $t Dissertation Abstracts International $g 78-08B(E).
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