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Research Article
Qingda Guo
South China University of Technology
Corresponding Author
ORCiD: https://orcid.org/0000-0001-5863-5541
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This work is licensed under a CC BY 4.0 License. Read Full License
Robots with visual sensors have been used in various goods logistics, such as bin picking or uploading. However, there are more and more demands for the automatic blanking and loading, it is necessary to solve the problem of object pose estimation in changing accommodation space. This paper proposes a method for pose estimation in the accommodation space using alpha-shape algorithm and improved Fruit fly Optimization Algorithm (FOA). The alpha-shape volume variety of object and measured space is set to the objective function and the pose variety of object is set to six variables of improved FOA. The experiments were performed by setting parameters of improved FOA and considering the four space types represented the common accommodation shapes. Compared with previous work using convex hull, the new study using alpha-shape algorithm not only keeps the object in the accommodation space, but also maintains the object pose is at the bottom of the space and can meet the practical requirement of object placement by robot arms.
Keywords
Robot, Pose estimation, Alpha-shape algorithm, Fruit fly optimization, Accommodation space
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Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 12 Apr, 2021
No community comments so far
Editorial decision: Minor Revision
On 05 Jul, 2021
Reviews received
Received 13 May, 2021
Reviewers invited
Invitations sent on 08 Apr, 2021
Editor assigned
On 10 Mar, 2021
First submitted
On 08 Mar, 2021
Metrics
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Subject Areas
Electrical Engineering
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A new preprint design is coming!
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This preprint is under consideration at Soft Computing. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research Article
Qingda Guo
South China University of Technology
Corresponding Author
ORCiD: https://orcid.org/0000-0001-5863-5541
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 12 Apr, 2021
No community comments so far
Editorial decision: Minor Revision
On 05 Jul, 2021
Reviews received
Received 13 May, 2021
Reviewers invited
Invitations sent on 08 Apr, 2021
Editor assigned
On 10 Mar, 2021
First submitted
On 08 Mar, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Electrical Engineering
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Robots with visual sensors have been used in various goods logistics, such as bin picking or uploading. However, there are more and more demands for the automatic blanking and loading, it is necessary to solve the problem of object pose estimation in changing accommodation space. This paper proposes a method for pose estimation in the accommodation space using alpha-shape algorithm and improved Fruit fly Optimization Algorithm (FOA). The alpha-shape volume variety of object and measured space is set to the objective function and the pose variety of object is set to six variables of improved FOA. The experiments were performed by setting parameters of improved FOA and considering the four space types represented the common accommodation shapes. Compared with previous work using convex hull, the new study using alpha-shape algorithm not only keeps the object in the accommodation space, but also maintains the object pose is at the bottom of the space and can meet the practical requirement of object placement by robot arms.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
The full text of this article is available to read as a PDF.
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