Visual Servoing Design and Control for Agriculture Robot; a Review

Dewi, Tresna; Risma, Pola; Oktarina, Yurni; Muslimin, Selamat

doi:10.1109/icecos.2018.8605209

Cited by 25 publications

(13 citation statements)

References 27 publications

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“…To achieve precise positioning of the start point, a secondary precision locating system is applied. Single fruit‐picking robots often adopt multiple positioning strategies (Dewi et al, 2018; Jin et al, 2020). The commonly used hand‐eye vision system is insufficient to achieve submillimeter accuracy, so a comprehensive servo control strategy was developed in conjunction with the laser ranging sensor.…”

Section: Discussionmentioning

confidence: 99%

Design, development, and field evaluation of a rubber tapping robot

Zhou

Zhang

et al. 2021

Journal of Field Robotics

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Modern robotics has made great strides in the field of agricultural harvesting. In the field of rubber tapping, however, there are still significant challenges to be faced. As one of the few agricultural harvesting areas primarily manual, rubber tapping requires precise control of the knife in the forest's unstructured environment at night. This paper presents the design of a rubber cutting robot for natural rubber plantations. An upgraded spatial spiral trajectory is established by analyzing the trunk and manual rubber cutting trajectories for the operation of a six‐axis tandem robot arm. A compact binocular stereo vision system achieved the initial perception of the parameters required for the cutting trajectory. Besides, an integrated end‐effector was developed to enable further precise perception of the cutting trajectory and cutting operations. The system was tested in the field at a rubber plantation in Hainan Province. The upgraded trajectory's adaptability and the accuracy and efficiency of the starting point positioning algorithm were verified. The operational performance of the complete system was evaluated to help guide future improvements. The error of the start point locating is 1.0 ± 0.1 mm, and the execution time is 17.01 ± 3.65 s. The bark consumption—cutting depth setting of (2.0 and 5.0 mm) is more appropriate for the rubber tapping robot. Then the accuracy of chip thickness and chip width is about 1.73 ± 0.28 mm, and 5.07 ± 0.13 mm, respectively. Furthermore, the accuracy of chip weight is 1.99 ± 0.24 mm. The average operating time of the whole tapping operation is 80 ± 5 s. Future work will include improvements in system stiffness and robustness. This study demonstrates the potential of applying industrial robotics to the field of latex harvesting. Robotics may be a future development towards mechanized rubber tapping.

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Section: Discussionmentioning

confidence: 99%

Design, development, and field evaluation of a rubber tapping robot

Zhou

Zhang

et al. 2021

Journal of Field Robotics

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“…An example of this is the work mentioned in [ 43 ] for the control of crop pests and diseases. Robots or robotic arms with camera equipment often referred to as visual servoing [ 45 ], have their own ‘eyes’ and use computer vision technology to perform task capture, making picking, irrigation, and application more precise. Thanks to the excellent computing power of artificial intelligence, the data can be processed in real-time and, through intelligent decision adjustment systems, the aim of optimizing the quality of the food can be achieved.…”

Section: Background Of Food Safetymentioning

confidence: 99%

Integration of Privacy Protection and Blockchain-Based Food Safety Traceability: Potential and Challenges

Lei

Liu

et al. 2022

Foods

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Concern about food safety has become a hot topic, and numerous researchers have come up with various effective solutions. To ensure the safety of food and avoid financial loss, it is important to improve the safety of food information in addition to the quality of food. Additionally, protecting the privacy and security of food can increase food harvests from a technological perspective, reduce industrial pollution, mitigate environmental impacts, and obtain healthier and safer food. Therefore, food traceability is one of the most effective methods available. Collecting and analyzing key information on food traceability, as well as related technology needs, can improve the efficiency of the traceability chain and provide important insights for managers. Technology solutions, such as the Internet of Things (IoT), Artificial Intelligence (AI), Privacy Preservation (PP), and Blockchain (BC), are proposed for food monitoring, traceability, and analysis of collected data, as well as intelligent decision-making, to support the selection of the best solution. However, research on the integration of these technologies is still lacking, especially in the integration of PP with food traceability. To this end, the study provides a systematic review of the use of PP technology in food traceability and identifies the security needs at each stage of food traceability in terms of data flow and technology. Then, the work related to food safety traceability is fully discussed, particularly with regard to the benefits of PP integration. Finally, current developments in the limitations of food traceability are discussed, and some possible suggestions for the adoption of integrated technologies are made.

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“…This type of robot has been so wellrecognized and well-researched that it creates a perfect worker for industry revolution 4.0 [5]. Automation has penetrated every aspect of human life to support our lifestyle or to spoil us [5,6,7,8,9,10,11,12,13,14,15], such as a service robot [6], a worker robot [7], and an agriculture robot [12,13,14,15,16,17].…”

Section: Introductionmentioning

confidence: 99%

“…Image processing is a key point for the visual cue of a robot used in a place where it is necessary to recognize an object, such as an agricultural robot [8,9,10,11,12,13,14,15,16,17]. Image processing is helpful in any agricultural situation, such as seeding [8][9], maintenance [18] [19], yield forecast [20][21], harvesting [12], and packaging [17,22,23,24,25,26,27].…”

Section: Introductionmentioning

confidence: 99%

Motion Control Analysis of Two Collaborative Arm Robots in Fruit Packaging System

Dewi

Anggraini

Risma

et al. 2021

Sinergi

Self Cite

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As robots' use increases in every sector of human life, the demand for cheap and efficient robots has also enlarged. The use of two or more simple robot is preferable to the use of one sophisticated robot. The agriculture industry can benefit from installing a robot, from seeding to the packaging of the product. A precise analysis is required for the installation of two collaborative robots. This paper discusses the motion control analysis of two collaborative arms robots in the fruit packaging system. The study begins with the relative motion analysis between two robots, starting with kinematics modeling, image processing for object detection, and the Fuzzy Logic Controller's design to show the relationship between the robot inputs and outputs. The analysis is carried out using SCILAB, open-source software for numerical computing engineering. This paper is intended as the initial analysis of the feasibility of the real experimental system.

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Visual Servoing Design and Control for Agriculture Robot; a Review

Cited by 25 publications

References 27 publications

Design, development, and field evaluation of a rubber tapping robot

Design, development, and field evaluation of a rubber tapping robot

Integration of Privacy Protection and Blockchain-Based Food Safety Traceability: Potential and Challenges

Motion Control Analysis of Two Collaborative Arm Robots in Fruit Packaging System

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