Deviation Tolerance Performance Evaluation and Experiment of Picking End Effector for Famous Tea

Zhu, Yao; Wu, Chuanyu; Tong, Junhua; Chen, Jianneng; Li, He; Wang, Rongyang; Jia, Jiangming

doi:10.3390/agriculture11020128

Cited by 21 publications

(8 citation statements)

References 22 publications

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“…The working resistance of a single cleaning wheel is about 35N, and there are two cleaning wheels in total [7] , as shown in figure 2: The normal walking speed of people who check the data is 5 km/h, but when only manpower is used, the weight will become larger, on the contrary, the speed will become smaller, taking 3.6 km/h, that is, Vm=1 m/s.…”

Section: Determination Of Working Resistancementioning

confidence: 99%

Structural Design of Leaf Sweeping Vehicle

Zhong,

Qiao

2024

Proceedings of the International Conference on Industrial Design and Environmental Engineering, IDEE 2023, November 24–26, 2023

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Leaf sweeping compressor is a new type of high efficiency sweeping equipment which integrates leaf sweeping, compression recovery and transportation. It can be widely used in the cleaning of urban residential areas, highways, parks and other areas. The design of this paper is a leaf sweeping compression device, the sweeping device, transmission device, compression device analysis and design. The collected leaves are compressed and processed into small solid pieces for easy transportation, storage and utilization. The cleaning roller is used to solve the problem of sticking to the conveyor belt on the surface of the residual leaf, and the working efficiency is improved by mechanical extrusion. In this design, the motion analysis and calculation of each mechanism are carried out, and the main parts are drawn, modeled and simulated by using Solidworks and other software to solve the problem of the coordination of the mechanism motion. The overall design realizes the intelligent automation of leaf litter collection, which will have broad application prospects in urban sanitation applications.

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Section: Determination Of Working Resistancementioning

confidence: 99%

Structural Design of Leaf Sweeping Vehicle

Zhong,

Qiao

2024

Proceedings of the International Conference on Industrial Design and Environmental Engineering, IDEE 2023, November 24–26, 2023

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“…Consequently, a bionic cutter was designed, and finite element analyses and cutting performance tests were conducted to optimize it. Zhu et al. (2021) designed a plucking device based on negative-pressure guidance for premium tea.…”

Section: Introductionmentioning

confidence: 99%

Continuous identification of the tea shoot tip and accurate positioning of picking points for a harvesting from standard plantations

Luo,

Zhang,

Cao

et al. 2023

Front. Plant Sci.

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To address the current problems of large positioning error, low picking efficiency, and high cost of tea shoot picking, a continuous and precise harvesting scheme for tea shoots based on a two-dimensional (2D) perspective is designed in this study. A high-speed harvesting method for tea shoots in a standardized tea plantation assembly line type was proposed. First, a 2D view recognition model of tea shoot tips in a multi-disturbance environment was constructed, and accurate picking point coordinates were determined by combining a skeleton algorithm and curve growth. To avoid the losses of recognition accuracy caused by the mistaken clamping of blades and vibrations during harvester operations, accurate control of the harvester was realized by combining path planning and the S-curve speed control function. The recognition accuracy for the verification set of the recognition model was 99.9%, and the mean average precision (0.5:0.95) value was 0.97. The test results show that the error between the actual picking point position and the position determined by the model was within ± 3 mm, and the picking success rate was 83.6%. Therefore, we can realize fast and accurate picking of tea shoots and lay the foundation for continuous tea picking in the future by simplifying the identification and picking process.

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“…Traditionally, tea harvesting has been performed by hand. However, with the increasing labor cost, lack of specialists, and higher quality requirements from tea producers, mechanized tea picking is becoming an inevitable trend for the sustainable development of the tea industry (Zhu et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Identification and picking point positioning of tender tea shoots based on MR3P-TS model

Yan

Lin

et al. 2022

Front. Plant Sci.

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Tea is one of the most common beverages in the world. In order to reduce the cost of artificial tea picking and improve the competitiveness of tea production, this paper proposes a new model, termed the Mask R-CNN Positioning of Picking Point for Tea Shoots (MR3P-TS) model, for the identification of the contour of each tea shoot and the location of picking points. In this study, a dataset of tender tea shoot images taken in a real, complex scene was constructed. Subsequently, an improved Mask R-CNN model (the MR3P-TS model) was built that extended the mask branch in the network design. By calculating the area of multiple connected domains of the mask, the main part of the shoot was identified. Then, the minimum circumscribed rectangle of the main part is calculated to determine the tea shoot axis, and to finally obtain the position coordinates of the picking point. The MR3P-TS model proposed in this paper achieved an mAP of 0.449 and an F2 value of 0.313 in shoot identification, and achieved a precision of 0.949 and a recall of 0.910 in the localization of the picking points. Compared with the mainstream object detection algorithms YOLOv3 and Faster R-CNN, the MR3P-TS algorithm had a good recognition effect on the overlapping shoots in an unstructured environment, which was stronger in both versatility and robustness. The proposed method can accurately detect and segment tea bud regions in real complex scenes at the pixel level, and provide precise location coordinates of suggested picking points, which should support the further development of automated tea picking machines.

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Deviation Tolerance Performance Evaluation and Experiment of Picking End Effector for Famous Tea

Cited by 21 publications

References 22 publications

Structural Design of Leaf Sweeping Vehicle

Structural Design of Leaf Sweeping Vehicle

Continuous identification of the tea shoot tip and accurate positioning of picking points for a harvesting from standard plantations

Identification and picking point positioning of tender tea shoots based on MR3P-TS model

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