Quad-Partitioning-Based Robotic Arm Guidance Based on Image Data Processing with Single Inexpensive Camera For Precisely Picking Bean Defects in Coffee Industry

Chen Ju Kuo, Ding Chau Wang, Pin Xin Lee, Tzu Ting Chen, Gwo Jiun Horng, Tz Heng Hsu, Zhi Jing Tsai, Mao Yuan Pai, Gen Ming Guo, Yu Chuan Lin, Min Hsiung Hung, Chao Chun Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, we propose a bean defect picking system with the quad-partitioning-based robotic arm guidance method, aimed at automatically and precisely picking bean defects in coffee industry. We assume the adopted inexpensive devices, including a robotic arm, a camera, and an IoT (Internet of Things) device, have only basic functions. For successfully picking the small size of beans as possible, stably moving the arm head to the target bean is the key technique in this topic. To achieve this goal under hardware limits, we design an iterative robotic arm guidance method to move the arm head close to the target with quad-partitioning relationships in the camera’s visual space by using image data processing techniques. The error distance after k iterations of the proposed method is approximately estimated as (Formula presented), where (Formula presented) and (Formula presented) are the width and the length of the field of view. We conduct a case study to validate the proposed method. Testing results show that the proposed system successfully picks bean defects with our proposed robotic arm guidance method.

Original languageEnglish
Title of host publicationIntelligent Information and Database Systems - 11th Asian Conference, ACIIDS 2019, Proceedings
EditorsTzung-Pei Hong, Ngoc Thanh Nguyen, Ngoc Thanh Nguyen, Bogdan Trawiński, Ford Lumban Gaol
PublisherSpringer Verlag
Pages152-164
Number of pages13
ISBN (Print)9783030148010
DOIs
Publication statusPublished - 2019 Jan 1
Event11th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2019 - Yogyakarta, Indonesia
Duration: 2019 Apr 82019 Apr 11

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11432 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2019
CountryIndonesia
CityYogyakarta
Period19-04-0819-04-11

Fingerprint

Robotic arms
Coffee
Bean
Guidance
Robotics
Partitioning
Image Processing
Defects
Camera
Cameras
Industry
Internet of Things
Target
Field of View
Hardware
Testing
Iteration

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Kuo, C. J., Wang, D. C., Lee, P. X., Chen, T. T., Horng, G. J., Hsu, T. H., ... Chen, C. C. (2019). Quad-Partitioning-Based Robotic Arm Guidance Based on Image Data Processing with Single Inexpensive Camera For Precisely Picking Bean Defects in Coffee Industry. In T-P. Hong, N. T. Nguyen, N. T. Nguyen, B. Trawiński, & F. L. Gaol (Eds.), Intelligent Information and Database Systems - 11th Asian Conference, ACIIDS 2019, Proceedings (pp. 152-164). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11432 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-030-14802-7_13
Kuo, Chen Ju ; Wang, Ding Chau ; Lee, Pin Xin ; Chen, Tzu Ting ; Horng, Gwo Jiun ; Hsu, Tz Heng ; Tsai, Zhi Jing ; Pai, Mao Yuan ; Guo, Gen Ming ; Lin, Yu Chuan ; Hung, Min Hsiung ; Chen, Chao Chun. / Quad-Partitioning-Based Robotic Arm Guidance Based on Image Data Processing with Single Inexpensive Camera For Precisely Picking Bean Defects in Coffee Industry. Intelligent Information and Database Systems - 11th Asian Conference, ACIIDS 2019, Proceedings. editor / Tzung-Pei Hong ; Ngoc Thanh Nguyen ; Ngoc Thanh Nguyen ; Bogdan Trawiński ; Ford Lumban Gaol. Springer Verlag, 2019. pp. 152-164 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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title = "Quad-Partitioning-Based Robotic Arm Guidance Based on Image Data Processing with Single Inexpensive Camera For Precisely Picking Bean Defects in Coffee Industry",
abstract = "In this paper, we propose a bean defect picking system with the quad-partitioning-based robotic arm guidance method, aimed at automatically and precisely picking bean defects in coffee industry. We assume the adopted inexpensive devices, including a robotic arm, a camera, and an IoT (Internet of Things) device, have only basic functions. For successfully picking the small size of beans as possible, stably moving the arm head to the target bean is the key technique in this topic. To achieve this goal under hardware limits, we design an iterative robotic arm guidance method to move the arm head close to the target with quad-partitioning relationships in the camera’s visual space by using image data processing techniques. The error distance after k iterations of the proposed method is approximately estimated as (Formula presented), where (Formula presented) and (Formula presented) are the width and the length of the field of view. We conduct a case study to validate the proposed method. Testing results show that the proposed system successfully picks bean defects with our proposed robotic arm guidance method.",
author = "Kuo, {Chen Ju} and Wang, {Ding Chau} and Lee, {Pin Xin} and Chen, {Tzu Ting} and Horng, {Gwo Jiun} and Hsu, {Tz Heng} and Tsai, {Zhi Jing} and Pai, {Mao Yuan} and Guo, {Gen Ming} and Lin, {Yu Chuan} and Hung, {Min Hsiung} and Chen, {Chao Chun}",
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editor = "Tzung-Pei Hong and Nguyen, {Ngoc Thanh} and Nguyen, {Ngoc Thanh} and Bogdan Trawiński and Gaol, {Ford Lumban}",
booktitle = "Intelligent Information and Database Systems - 11th Asian Conference, ACIIDS 2019, Proceedings",
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Kuo, CJ, Wang, DC, Lee, PX, Chen, TT, Horng, GJ, Hsu, TH, Tsai, ZJ, Pai, MY, Guo, GM, Lin, YC, Hung, MH & Chen, CC 2019, Quad-Partitioning-Based Robotic Arm Guidance Based on Image Data Processing with Single Inexpensive Camera For Precisely Picking Bean Defects in Coffee Industry. in T-P Hong, NT Nguyen, NT Nguyen, B Trawiński & FL Gaol (eds), Intelligent Information and Database Systems - 11th Asian Conference, ACIIDS 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11432 LNAI, Springer Verlag, pp. 152-164, 11th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2019, Yogyakarta, Indonesia, 19-04-08. https://doi.org/10.1007/978-3-030-14802-7_13

Quad-Partitioning-Based Robotic Arm Guidance Based on Image Data Processing with Single Inexpensive Camera For Precisely Picking Bean Defects in Coffee Industry. / Kuo, Chen Ju; Wang, Ding Chau; Lee, Pin Xin; Chen, Tzu Ting; Horng, Gwo Jiun; Hsu, Tz Heng; Tsai, Zhi Jing; Pai, Mao Yuan; Guo, Gen Ming; Lin, Yu Chuan; Hung, Min Hsiung; Chen, Chao Chun.

Intelligent Information and Database Systems - 11th Asian Conference, ACIIDS 2019, Proceedings. ed. / Tzung-Pei Hong; Ngoc Thanh Nguyen; Ngoc Thanh Nguyen; Bogdan Trawiński; Ford Lumban Gaol. Springer Verlag, 2019. p. 152-164 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11432 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - Quad-Partitioning-Based Robotic Arm Guidance Based on Image Data Processing with Single Inexpensive Camera For Precisely Picking Bean Defects in Coffee Industry

AU - Kuo, Chen Ju

AU - Wang, Ding Chau

AU - Lee, Pin Xin

AU - Chen, Tzu Ting

AU - Horng, Gwo Jiun

AU - Hsu, Tz Heng

AU - Tsai, Zhi Jing

AU - Pai, Mao Yuan

AU - Guo, Gen Ming

AU - Lin, Yu Chuan

AU - Hung, Min Hsiung

AU - Chen, Chao Chun

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N2 - In this paper, we propose a bean defect picking system with the quad-partitioning-based robotic arm guidance method, aimed at automatically and precisely picking bean defects in coffee industry. We assume the adopted inexpensive devices, including a robotic arm, a camera, and an IoT (Internet of Things) device, have only basic functions. For successfully picking the small size of beans as possible, stably moving the arm head to the target bean is the key technique in this topic. To achieve this goal under hardware limits, we design an iterative robotic arm guidance method to move the arm head close to the target with quad-partitioning relationships in the camera’s visual space by using image data processing techniques. The error distance after k iterations of the proposed method is approximately estimated as (Formula presented), where (Formula presented) and (Formula presented) are the width and the length of the field of view. We conduct a case study to validate the proposed method. Testing results show that the proposed system successfully picks bean defects with our proposed robotic arm guidance method.

AB - In this paper, we propose a bean defect picking system with the quad-partitioning-based robotic arm guidance method, aimed at automatically and precisely picking bean defects in coffee industry. We assume the adopted inexpensive devices, including a robotic arm, a camera, and an IoT (Internet of Things) device, have only basic functions. For successfully picking the small size of beans as possible, stably moving the arm head to the target bean is the key technique in this topic. To achieve this goal under hardware limits, we design an iterative robotic arm guidance method to move the arm head close to the target with quad-partitioning relationships in the camera’s visual space by using image data processing techniques. The error distance after k iterations of the proposed method is approximately estimated as (Formula presented), where (Formula presented) and (Formula presented) are the width and the length of the field of view. We conduct a case study to validate the proposed method. Testing results show that the proposed system successfully picks bean defects with our proposed robotic arm guidance method.

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U2 - 10.1007/978-3-030-14802-7_13

DO - 10.1007/978-3-030-14802-7_13

M3 - Conference contribution

AN - SCOPUS:85064556886

SN - 9783030148010

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 152

EP - 164

BT - Intelligent Information and Database Systems - 11th Asian Conference, ACIIDS 2019, Proceedings

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PB - Springer Verlag

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Kuo CJ, Wang DC, Lee PX, Chen TT, Horng GJ, Hsu TH et al. Quad-Partitioning-Based Robotic Arm Guidance Based on Image Data Processing with Single Inexpensive Camera For Precisely Picking Bean Defects in Coffee Industry. In Hong T-P, Nguyen NT, Nguyen NT, Trawiński B, Gaol FL, editors, Intelligent Information and Database Systems - 11th Asian Conference, ACIIDS 2019, Proceedings. Springer Verlag. 2019. p. 152-164. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-14802-7_13