Design and experiment of a picking robot for Agaricus bisporus based on machine vision
Keywords:
Agaricus bisporus, picking platform, machine vision, robotAbstract
Harvesting represents the crucial stage in the cultivation process of Agaricus bisporus mushrooms. An important way for the production process of Agaricus bisporus to reduce costs and increase income is to ensure timely harvest of Agaricus bisporus, reduce harvesting costs, and improve harvesting efficiency. There are many disadvantages in manual picking, such as high labor intensity, time-consuming work and high cost. In this study, a set of mushroom picking platform including climbing mechanism, picking robot, and control system was designed and developed. The picking robot consisted of a truss mechanism, an image acquisition device, a mushroom collection device, and a picking actuator. The profile picking actuator could realize the function of constant force clamping. An online size detection algorithm for Agaricus bisporus based on deep image processing was proposed. The algorithm included removal of abnormal noise points, background segmentation, coordinate conversion, and diameter detection. The precision picking system for Agaricus bisporus with coordinate compensation function controlled by Industrial Personal Computer was designed, and the visual control interface was developed based on Labview. Through the performance test, the reliability of machine vision recognition and the overall operating stability of the picking platform were verified. The test results showed that in the process of machine vision recognition, the recognition accuracy rate was higher than 92.50%, the missed detection rate was lower than 4.95%, the false detection rate was lower than 2.15%, and the diameter measurement error was less than 4.50%. The image processing algorithm had high recognition rate and small diameter measurement error, which could meet the requirements of picking operation. The picking platform’s picking success rate was higher than 95.45%, the picking damage rate was lower than 3.57%, and the picking output rate was higher than 87.09%. Compared with manual picking, the recognition accuracy rate of the picking platform was increased by 6.70%, the picking output rate was increased by 1.51%. The overall performance of the picking platform was stable and practical. Key words: Agaricus bisporus; picking platform; machine vision; robot DOI: 10.25165/j.ijabe.20241704.7740 Citation: Ji J T, Du S C, Li M S, Zhu X F, Zhao K X, Zhang S H, et al. Design and experiment of a picking robot for Agaricus bisporus based on machine vision. Int J Agric & Biol Eng, 2024; 17(4): 67–76.References
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[2] Geng Y C, Zhang T, Liu H B, Zhai L M, Yang B, Wang H Y. Effects of different briquetting modes on production of Agaricus bisporus. Transactions of the CSAE, 2016; 32(Z2): 275–278. (in Chinese)
[3] Radzki W, Ziaja-Sołtys M, Nowak J, Topolska J, Bogucka-Kocka A, Sławińska A, et al. Impact of processing on polysaccharides obtained from button mushroom (Agaricus bisporus). International Journal of Food Science & Technology, 2019; 54(4): 1405–1412.
[4] Dai F, Yang J, Zhao W Y, Li Z G, Xin S L, Zhang F W. Design and experiment of key assorted device based on factory production of Agaricus bisporus. Transactions of the CSAE, 2018; 34(6): 43–51. (in Chinese)
[5] Shamshiri R R, Kalantari F, Ting K C, Thorp K R, Hameed I A, Weltzien C, et al. Advances in greenhouse automation and controlled environment agriculture: A transition to plant factories and urban agriculture. Int J Agric & Biol Eng, 2018; 11(1): 1–22.
[6] Wang Z Z, Li X F, Song S X, Liu M Y, Dong T. The progress of the research on the pretreatment and preservation of the Agaricus bisporus. Food Research and Development, 2018; 39(4): 200–206.
[7] Liu J, Wu Y C, Kan J, Wang Y, Jin C H. Changes in reactive oxygen species production and antioxidant enzyme activity of Agaricus bisporus harvested at different stages of maturity. Journal of the Science of Food and Agriculture, 2013; 93(9): 2201–2206.
[8] Cheng D H. Design and analysis of the end effector for Agaricus bisporus harvesting manipulator. Mechatronics Information, 2020. pp.68–69.
[9] Lee C H, Choi D, Pecchia J, He L, Heinemann P. Development of a mushroom harvesting assistance system using computer vision. 2019 ASABE Annual International Meeting, Boston: ASABE, 2019; Paper No. 1900505.
[10] Tillett R. D, Batchelor B G. An algorithm for locating mushrooms in a growing bed. Computers and Electronics in Agriculture, 1991; 6(3): 191–200.
[11] Yu G H, Luo J M, Zhao Y. Region marking technique based on sequential scan and segmentation method of mushroom images. Transactions of the CSAE, 2006; 22(4): 139–142.
[12] Yu G H, Zhao Y, Li G, Shi H. Algorithm for locating individual mushroom and description of its contour using machine vision. Transactions of the CSAE, 2005; 21(6): 101–104. (in Chinese)
[13] Yang Y Q, Ye M, Lu Y H, Ren S G. Localization algorithm based on corner density detection for overlapping mushroom image. Computer Systems and Applications, 2018; 27(5): 119–125.
[14] Wang F Y, Feng W J, Zheng J Y, Sun J B, Niu L Y, Chen Z X, et al. Design and experiment of automatic sorting and grading system based on machine vision for white agaricus bisporus. Transactions of the CSAE, 2018; 34(7): 256–263. (in Chinese)
[15] Wang F, Zheng J, Tian X, Wang J, Niu L, Feng W. An automatic sorting system for fresh white button mushrooms based on image processing. Computers and Electronics in Agriculture. 2018; 151: 416–425.
[16] Wang L, Xu W, Du K W, Lu W, Zhu J H, Zhang J. Portabella mushrooms measurement in situ based on SR300 depth camera. Transactions of the CSAM, 2018; 49(12): 13–19, 108. (in Chinese)
[17] Hu X, Pan Z R, Yang S Z, Tao Y. Study on the control system of Agaricus bisporus picking robot. Journal of Physics: Conference Series, 2019; 1187(3): 032033.
[18] Hu X, Wang C, Tao Y. Design and application of visual system in the Agaricus bisporus picking robot. Journal of Physics: Conference Series, 2019; 1187(3): 032034.
[19] Hu X, Pan Z R, Lyu S K. Picking path optimization of Agaricus bisporus picking robot. Mathematical Problems in Engineering, 2019; 2019: 8973153.
[20] Reed J N, Miles S J, Butler J, Baldwin M, Noble R. AE - automation and emerging technologies: automatic mushroom harvester development. Journal of Agricultural Engineering Research, 2001; 78(1): 15–23. (in Chinese)
[21] NY/T 1790-2009. Grades and specifications of Agaricus bisporus. Industry Standards for Agriculture, 2009. (in Chinese)
[22] Sun J W, Zhao K X, Ji J T, Zhu X F, Ma H. Detection and diameter measurement method of Agaricus bisporus based on “submerged method”. Journal of Agricultural Mechanization Research, 2021; 43(2): 28–33. (in Chinese)
[23] Ding L, Goshtasby A. On the Canny edge detector. Pattern Recognition, 2001; 34(3): 721–725.
[24] Feng Q C, Zhao C J, Wang X N, Wang X, Gong L, Liu C L. Fruit bunch measurement method for cherry tomato based on visual servo. Transactions of the CSAE, 2015; 31(16): 206–212. (in Chinese)
[25] Xu X L, Tao H, Li C J, Cheng C, Guo H, Zhou J P. Detection and location of pine wilt disease induced dead pine trees based on faster R-CNN. Transactions of the CSAM, 2020; 51(7): 228–236. (in Chinese)
[26] Xiong J T, Lin R, Liu Z, He Z L, Yang Z G, Bu R B. Visual Technology of Picking Robot to Detect Litchi at Nighttime under Natural Environment. Transactions of the CSAM, 2017; 48(11): 28–34. (in Chinese)
[27] Vera E, Lucio D, Fernandes L A F, Velho L. Hough Transform for real-time plane detection in depth images. Pattern Recognition Letters, 2018; 103: 8–15.
[28] Wang G L, Liu W C, Wang A, Bai K K, Zhou H B. Design and experiment on intelligent reseeding devices for rice tray nursing seedling based on machine vision. Transactions of the CSAE, 2018; 34(13): 35–42. (in Chinese)
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Published
2024-09-06
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Ji, J., Du, S., Li, M., Zhu, X., Zhao, K., Zhang, S., & Ji, X. (2024). Design and experiment of a picking robot for Agaricus bisporus based on machine vision. International Journal of Agricultural and Biological Engineering, 17(4), 67–76. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/7740
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Power and Machinery Systems
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