Autonomous navigation for a wolfberry picking robot using visual cues and fuzzy control
Lycium barbarum commonly known as wolfberry or Goji is considered an important ingredient in Japanese, Korean, Vietnamese, and Chinese food and medicine. It is cultivated extensively in these countries and is usually harvested manually, which is labor-intensive and tedious task. To improve the effic...
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KeAi Communications Co., Ltd.
2021-03-01
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doaj-283a3e2fe05b44688abf32475024c5c02021-03-11T04:24:53ZengKeAi Communications Co., Ltd.Information Processing in Agriculture2214-31732021-03-01811526Autonomous navigation for a wolfberry picking robot using visual cues and fuzzy controlYue Ma0Wenqiang Zhang1Waqar S. Qureshi2Chao Gao3Chunlong Zhang4Wei Li5College of Engineering, China Agricultural University, ChinaCollege of Engineering, China Agricultural University, China; Corresponding author at: Room 549, China Agricultural University, Beijing, China.Department of Mechatronics Engineering, National University of Sciences and Technology, H-12 Islamabad, PakistanCollege of Engineering, China Agricultural University, ChinaCollege of Engineering, China Agricultural University, ChinaCollege of Engineering, China Agricultural University, ChinaLycium barbarum commonly known as wolfberry or Goji is considered an important ingredient in Japanese, Korean, Vietnamese, and Chinese food and medicine. It is cultivated extensively in these countries and is usually harvested manually, which is labor-intensive and tedious task. To improve the efficiency of harvesting and reduce manual labor, automatic harvesting technology has been investigated by many researchers in recent years. In this paper, an autonomous navigation algorithm using visual cues and fuzzy control is proposed for Wolfberry orchards. At first, we propose a new weightage (2.4B-0.9G-R) to convert a color image into a grayscale image for better identification of the trunk of Lycium barbarum, the minimum positive circumscribed rectangle is used to describe the contours. Then, using the contour points the least square method is used to fit the navigation line and a region of interest (ROI) is computed that improves the real-time accuracy of the system. Finally, a set of fuzzy controllers, for pneumatic steering system, is designed to achieve real-time autonomous navigation in wolfberry orchard. Static image experiments show that the average accuracy rate of the algorithm is above 90%, and the average time consumption is approximately 162 ms, with good robustness and real-time performance. The experimental results show that when the speed is 1 km/h, the maximum lateral deviation is less than 6.2 cm and the average lateral deviation is 2.9 cm, which meets the requirements of automatic picking of wolfberry picking robot in real-world environments.http://www.sciencedirect.com/science/article/pii/S2214317319303269Visual navigationChinese wolfberry pickingFuzzy control |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yue Ma Wenqiang Zhang Waqar S. Qureshi Chao Gao Chunlong Zhang Wei Li |
spellingShingle |
Yue Ma Wenqiang Zhang Waqar S. Qureshi Chao Gao Chunlong Zhang Wei Li Autonomous navigation for a wolfberry picking robot using visual cues and fuzzy control Information Processing in Agriculture Visual navigation Chinese wolfberry picking Fuzzy control |
author_facet |
Yue Ma Wenqiang Zhang Waqar S. Qureshi Chao Gao Chunlong Zhang Wei Li |
author_sort |
Yue Ma |
title |
Autonomous navigation for a wolfberry picking robot using visual cues and fuzzy control |
title_short |
Autonomous navigation for a wolfberry picking robot using visual cues and fuzzy control |
title_full |
Autonomous navigation for a wolfberry picking robot using visual cues and fuzzy control |
title_fullStr |
Autonomous navigation for a wolfberry picking robot using visual cues and fuzzy control |
title_full_unstemmed |
Autonomous navigation for a wolfberry picking robot using visual cues and fuzzy control |
title_sort |
autonomous navigation for a wolfberry picking robot using visual cues and fuzzy control |
publisher |
KeAi Communications Co., Ltd. |
series |
Information Processing in Agriculture |
issn |
2214-3173 |
publishDate |
2021-03-01 |
description |
Lycium barbarum commonly known as wolfberry or Goji is considered an important ingredient in Japanese, Korean, Vietnamese, and Chinese food and medicine. It is cultivated extensively in these countries and is usually harvested manually, which is labor-intensive and tedious task. To improve the efficiency of harvesting and reduce manual labor, automatic harvesting technology has been investigated by many researchers in recent years. In this paper, an autonomous navigation algorithm using visual cues and fuzzy control is proposed for Wolfberry orchards. At first, we propose a new weightage (2.4B-0.9G-R) to convert a color image into a grayscale image for better identification of the trunk of Lycium barbarum, the minimum positive circumscribed rectangle is used to describe the contours. Then, using the contour points the least square method is used to fit the navigation line and a region of interest (ROI) is computed that improves the real-time accuracy of the system. Finally, a set of fuzzy controllers, for pneumatic steering system, is designed to achieve real-time autonomous navigation in wolfberry orchard. Static image experiments show that the average accuracy rate of the algorithm is above 90%, and the average time consumption is approximately 162 ms, with good robustness and real-time performance. The experimental results show that when the speed is 1 km/h, the maximum lateral deviation is less than 6.2 cm and the average lateral deviation is 2.9 cm, which meets the requirements of automatic picking of wolfberry picking robot in real-world environments. |
topic |
Visual navigation Chinese wolfberry picking Fuzzy control |
url |
http://www.sciencedirect.com/science/article/pii/S2214317319303269 |
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