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International Conference on Control, Automation and systems ( ICCAS)

作者： Yonghyun Park Hyoung Il Son Department of Convergence Biosystems Engineering Chonnam National University Gwangju Korea Interdisciplinary Program in IT-Bio Convergence System Chonnam National University Gwangju Korea Research Center for Biological Cybernetics Chonnam National University Gwangju Korea

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

This study introduces an system designed to cooperative control for agricultural dual-arm robots through visual scene understanding. Leveraging images, the system constructs scene graphs and assigns weights to various object attributes, enabling the identification of the most efficient sequence for performing harvesting tasks. Key factors, such as object ripeness, size, and accessibility, are considered to enhance the precision and productivity of robotic harvesting operations. Experimental validation demonstrates the potential of the proposed system in robotic harvesting and promoting advancements in smart agriculture. Future work will be focused on integrating deep learning models for improved object detection, coupling the system with control mechanisms for dual-arm robots to enable seamless task execution, and extending its application to various agricultural tasks beyond harvesting.

关键词： Deep learning Smart agriculture Productivity Couplings Visualization Object detection Control systems Resource management Object recognition Robots

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Robust Visual Servoing Algorithm-based Cucumis-melo Harvesting Robot

Robust Visual Servoing Algorithm-based Cucumis-melo Harvesti...

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International Conference on Control, Automation and systems ( ICCAS)

作者： Woojun Park Yonghyun Park Changjo Kim Hyoung Il Son Department of Convergence Biosystems Engineering Chonnam National University Gwangju Korea Interdisciplinary Program in IT-Bio Convergence System Chonnam National University Gwangju Korea Research Center for Biological Cybernetics Chonnam National University Gwangju Korea

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

Harvesting robots are performed in unpredictable and unstructured environments. Visual servoing is being researched and developed to enhance the ability to perform tasks in real-time within such environments. It is essential to accurately estimate the pose and move to the desired location to harvest the fruit. In this study, we utilized image stabilization(IS) to obtain stable images and proposed a curvature-based modeling method for the fruit and pedicel to apply it to various fruits and vegetables. The main objective of this study is to perform detection and 6D pose estimation that can be applied to various fruits using deep learning-based fruit detection. The proposed algorithm will be validated by evaluating its performance on cucumis-melo in a laboratory environment. Through this evaluation, it has been confirmed that it can be applied to cucumis-melo, and if the proposed system is used, it can be applied to other fruits. The experimental results will serve as foundational data for assessing the possibility of applying this system in real farms in the future.

关键词： Automation Pose estimation Laboratories Feature extraction Control systems Visual servoing Real-time systems Robots

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Three-axis attitude control of chinese cabbage harvester cutting device based on sensor fusion

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Journal of Institute of Control, Robotics and systems 2021年第3期27卷 277-284页

作者： Park, Yonghyun Jun, Jongpyo Son, Hyoung Il Department of Biosystems Engineering Gyeongsang National University Korea Republic of Department of Rural and Biosystemss Engineering Chonnam National University Korea Republic of Interdisciplinary Program in IT-Bio Convergence System Chonnam National University Korea Republic of

In Korea, Chinese cabbage harvesting is insufficiently mechanized and automated, and this task is typically carried out using manual labor. Thus, research on Chinesee cabbage harvesters is required. However, the terrain in cabbage fields is generally rough and comprises many obstacles. Consequently, problems such as overcutting, missed cutting, and side cutting occur while cutting cabbages using a cabbage harvester. Therefore, it is necessary to study the cutting mechanism of the harvester to perform accurate cutting, considering the terrain in the fields. To this end, a three-axis attitude control mechanism was designed in this study;this mechanismm controls the cutting device of the Korean cabbage harvester with three cylinders. In addition, an accelerometer, a gyro sensor, and a rotary encoder were designed for sensor fused. The cylinders were controlled such that the measured roll () and pitch (θ) were level with the ground. In addition, the angle of the guide in the cutting device (θe), driven by grounding to the ground, was calibrated using the height data. The cylinder in the sliding (x) axis was controlled to maintain the target height. Further, a proportional-integral-derivative controller was integrated to reduce overshoot and improve stability. To assess the performancee of the algorithm, a 2:1 scaled-down model of the cutting device of the Korean cabbage harvester was produced, and the attitude control mechanism was installed on its driving platform and tested. Attitude measurement was performed using a motion capture device (OptiTrack). For quantitative evaluation, data with and without the attitude control system were compared by estimating their root mean square error (RMSE). The RMSE values for the level and height were 0.89° and 2.23 cm, respectively, for attitude control with the posture control system;however, those for attitude control without the posture control system weree 2.15° and 4.05 cm, respectively. In addition, improvements of 58% in th

关键词： Three term control systems

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A GNN-based Decentralized Path Planning for Agricultural Robot Team: Work in Progress

A GNN-based Decentralized Path Planning for Agricultural Rob...

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International Conference on Control, Automation and systems ( ICCAS)

作者： Yuseung Jo Hyoung Il Son Department of Convergence Biosystems Engineering Chonnam National University Gwangju Korea Interdisciplinary Program in IT-Bio Convergence System Chonnam National University Gwangju Korea Research Center for Biological Cybernetics Chonnam National University Gwangju Korea

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

In a wide, dense, and unstructured agricultural environment, the deployment of autonomous mobile robots is an attractive option. In such the environment, large robot systems are subject to physical limitations such as communication distance and sensor measurements. This limitation is solved effectively with distributed path planning and coordination. A graph neural networks (GNNs) are an effective approach for efficient communication of multi-robot systems. In this paper, we propose a GNN-based decentralized path planning framework for agricultural robot team. The proposed model used a graph neural network for responsiveness to dynamic environmental changes, scalability, and efficient local information exchange among the adjacent agents. A graph neural network takes as input the observable features (e.g., states, subgoal, obstacle) of each agent for a partial observation scenario. As the action policy to predict the behavior of the agents, the model trained the tradition optimal multi-agent pathfinding algorithm, conflict-based search algorithm. Through the simulation-based validation, the model was confirmed to have performance comparable to existing expert algorithms, responsiveness to dynamic environments, and scalability.

关键词： Agricultural robots Adaptation models Heuristic algorithms Computational modeling Scalability Prediction algorithms Robot sensing systems Graph neural networks Path planning Testing

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Optimization of Workspace Partitioning using Weighted Voronoi Diagram for Fleet of Autonomous Tractors

Optimization of Workspace Partitioning using Weighted Vorono...

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International Conference on Control, Automation and systems ( ICCAS)

作者： Changjo Kim Hyoung Il Son Department of Convergence Biosystems Engineering Chonnam National University Gwangju Republic of Korea Interdisciplinary Program in IT-Bio Convergence System Chonnam National University Gwangju Republic of Korea Research Center for Biological Cybernetics Chonnam National University Gwangju Republic of Korea

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

The automation of agricultural systems is essential for enhancing productivity and ensuring sustainable food production. The introduction of autonomous tractors and fleet of autonomous tractors technology is important to the advancement of agricultural automation. This paper proposes an optimization method for workspace partitioning using a weighted voronoi diagram for fleet of autonomous tractors. The proposed method generates a node map based on an orchard environment, determines the centers of the areas to partition the workspace to be assigned to the k tractors, sets weights based on the specifications of each tractor, optimizes these weights, and partition the workspace to maximize work *** study validated the performance of workspace partitioning optimization through simulations and field evaluations. The results of this study expect that the proposed method can be applied to fleet of autonomous tractors technology to improve the efficiency of agricultural work.

关键词： Productivity Automation Food manufacturing Scalability Optimization methods Agricultural machinery Control systems Robots

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Field Evaluation of a Prioritized Path-Planning Algorithm for Heterogeneous Agricultural Tasks of Multi-UGVs

Field Evaluation of a Prioritized Path-Planning Algorithm fo...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Yuseung Jo Hyoung Il Son Department of Convergence Biosystems Engineering Chonnam National University Gwangju Republic of Korea Interdisciplinary Program in IT-Bio Convergence System Chonnam National University Gwangju Republic of Korea Research Center for Biological Cybernetics Chonnam National University Gwangju Republic of Korea

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper introduces a prioritized path-planning algorithm for heterogeneous tasks performed by multiple unmanned ground vehicles (UGVs) in agricultural environments. The algorithm considers varying robot priorities, thereby extending the traditional multi-agent path finding (MAPF) approach. The proposed algorithm is evaluated in scenarios occurring during representative agricultural operations: harvesting and transportation. An experimental validation is conducted in agriculture-like settings by using multiple simultaneous localization and mapping systems and navigation systems. The results revealed that the path of agent 1 , which was assigned the highest priority in both the indoor and outdoor environments, was shortened considerably (3.38 m, 3.6 m, and 5.6 m, respectively). Especially in the face scenario, the sum of changes in distance, calculated using the proposed algorithm was negative, meaning that traffic congestion in the multi-robot system used in the experiment was alleviated without the need for inter-robot communication.

关键词： Simultaneous localization and mapping Navigation Transportation Symbols Path planning Reliability Task analysis

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Performance Comparison Study of Cherry Tomato Ripeness Detection Using Multiple YOLO Models

引用

Journal of Institute of Control, Robotics and systems 2024年第11期30卷 1214-1220页

作者： Yang, Dayeon Son, Hyoung Il Ju, Chanyoung Department of Convergence Biosystems Engineering Chonnam National University Korea Republic of Interdisciplinary Program in IT-Bio Convergence System Chonnam National University Korea Republic of Research Center for Biological Cybernetics Chonnam National University Korea Republic of Purpose Built Mobility Group Korea Institute of Industrial Technology Korea Republic of

Millions of tons of cherry tomatoes are produced annually, with the harvesting process being crucial. This paper presents a deep learning-based approach to distinguish the ripeness of cherry tomatoes during the harvesting process. It specifically analyzes the performance of the YOLO (You Only Look Once)v5 and YOLOv8 models, which are designed to rapidly detect the ripeness of cherry tomatoes in real time. The proposed system is expected to resolve rural issues caused by population decline and enhance productivity in cherry tomato harvesting environments. Future research will aim to apply this technology to harvesting robots for the automatic recognition and harvesting of cherry tomatoes. © 2024, Institute of Control, Robotics and systems. All rights reserved.

关键词： Fruits

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A sensor fusion-based cutting device attitude control to improve the accuracy of korean cabbage harvesting

arXiv

引用

arXiv 2021年

作者： Park, Yonghyun Son, Hyoung Il Department of Rural and Biosystems Engineering Chonnam National University Yongbong-ro 77 Gwangju61186 Korea Republic of Interdisciplinary Program in IT-Bio Convergence System Chonnam National University Yongbong-ro 77 Gwangju61186 Korea Republic of

Korean cabbage harvesting lacks mechanization and depends on human power;thus, conducting research on Korean cabbage harvesters is of immense importance. Although these harvesters have been developed in various forms, they have not yet attained commercialization. Most Korean cabbage fields have slopes;thus there are several challenges, that can prevent accurate harvesting. Therefore, to address these challenges at the site, we adopt two cylinders in this study, develop a mechanism that enables attitude control of the cutting device, not driving platform body, to cope with slopes. By maintaining the level, angle, height of cutting, we can reduce loss and improve harvest performance. It is difficult to find examples where these mechanisms have been applied. For basic research, sensor fusion has been carried out based on the Kalman filter, which is commonly utilized for attitude control. The hydraulic cylinder was controlled using the data obtained for maintaining the attitude. Furthermore, field tests were conducted to validate this system, and the root mean square error (RMSE) was obtained and verified to quantitatively assess the presence or absence of attitude control. Therefore, the purpose of this study is to suggest a development direction for Korean cabbage harvesters via the proposed attitude control system. Copyright © 2021, The Authors. All rights reserved.

关键词： Kalman filters

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Field Evaluations of A Deep Learning-based Intelligent Spraying Robot with Flow Control for Pear Orchards

arXiv

引用

arXiv 2021年

作者： Seol, Jaehwi Kim, Jeongeun Son, Hyoung Il Department of Rural and Biosystems Engineering Chonnam National University Yongbong-ro 77 Gwangju61186 Korea Republic of Interdisciplinary Program in IT-Bio Convergence System Chonnam National University Yongbong-ro 77 Gwangju61186 Korea Republic of

This paper proposes a variable flow control system in real time with deep learning using the segmentation of fruit trees in a pear orchard. The flow rate control in real time, undesired pressure fluctuation and theoretical modeling may differ from those in the real world. Therefore, two types of preliminary experiments were designed to examine the linear relationship of the flow rate modeling. Through a preliminary experiment, the parameters of the pulse width modulation (PWM) controller were optimized, and an actual field experiment was conducted to confirm the performance of the variable flow rate control system. As a result of the field experiment, the performance of the proposed system was satisfactory, as it showed that it could reduce pesticide use and the risk of pesticide exposure. Especially, since the field experiment was conducted in an unstructured environment, the proposed variable flow control system is expected to be sufficiently applicable to other orchards. © 2021, CC BY.

关键词： Pulse width modulation

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Calculation of Seasonal Thermal Energy Storage system Capacity for Melon Greenhouse Using Energy Analysis program

SSRN

引用

SSRN 2024年

作者： Park, Sungwan Seonwoo, Hoon Sunchon National University Suncheon57922 Korea Republic of Department of Convergent Biosystems Engineering College of Life Science and Natural Resources Sunchon National University Suncheon57922 Korea Republic of Interdisciplinary Program in IT-Bio Convergence System Sunchon National University Suncheon57922 Korea Republic of

Carbon dioxide (CO₂), one of major reason of global warming and climate change, is predominantly cultivated in greenhouses which require significant fossil fuel consumption for heating during the winter season. There is a need to implement facilities that utilize renewable energy to heat greenhouses and reduce carbon emissions. In this study, the application of seasonal thermal energy storage (STES) using renewable energy sources in single- and double-layer melon greenhouses was investigated using building energy simulation (BES) software, specifically the transient system simulation tool (TRNSYS, Ver 18, USA). The double-layered greenhouse reduced the cooling load by 17.8% and the heating load by 61.6% compared to the single-layered greenhouse. The solar collector and storage tank capacity of the double-layer greenhouse was reduced by 25-46% and 37-60%, respectively, compared to the single-layered greenhouse. The single-layered greenhouse required the area of the solar collector of 20 m², the volume of the storage tank of 200 m³ and the pump flow rate of 3000 kg/h. The research can contribute to the selection of solar collectors and storage tanks of appropriate capacity for greenhouses implementing STES in the future. Consequently, it can promote sustainable agricultural practices by reducing fossil fuel consumption and mitigating greenhouse gas emissions. © 2024, The Authors. All rights reserved.

关键词： Greenhouses

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