• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.463-466
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• 2002

The Field Robot means the machinery applied for outdoor tasks in construction, agriculture and undersea etc. In this paper, to field-robotize a hydraulic excavator, we have proposed a robust and systematic controller design method. Disturbance observer is used as inner controller to reshape the excavating system into the linear dynamics of nominal model by compensating coupled nonlinear terms, model uncertainties and external load variations. Using the linear model that is obtained through off-line system identification, a H control scheme is applied to construct a disturbance observer and a servo-controller systematically.

• Journal of Biosystems Engineering
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• v.32 no.5
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• pp.339-347
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• 2007

A hexapod walking robot had been developed for gathering information in the field. The developed robot was $260{\times}260{\times}130$ ($W{\times}L{\times}H$, mm) in size and 14.7 N in weight. The legs had nineteen degrees of freedom. A leg has three rotational joints actuated by small servomotors. Two servomotors placed at ankle and knee played the roles of vertical joint for up and down motions of the leg and the other one placed at coxa played the role of horizontal joint for forward and backward motions. In addition, a servomotor placed at thorax between the front legs and the middle legs played the role of vertical joint for pumping the two front legs to climb stair or inclination. Walking motion of the robot was executed by tripod gait. The robot was controlled by manual remote-controller communicated by an infrared ray. Two controllers were equipped to control the walking of the robot. The sub-controller using PIC microcomputer (Microchips, PIC16F84A) received the 16 bit command signal from the manual remote controller, decoded it to 8bit and transmitted it to the main microcomputer (RENESAS, SH2/7045), which controlled the 19 servomotors using the PWM command signals. Walking speeds were controlled by adjusting the period of command cycle and the stride. Forward walking speed were within 100 cm/min to 300 cm/min. However, experimental walking speed had the error of 4-40 cm/min to compare with the theoretical one, because of slippage of the leg and the circular arc motion of servomotor of coxa.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.167-168
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• 2009

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• v.10 no.1
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• pp.377-384
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• 2005

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• v.10 no.1
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• pp.369-376
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• 2005

• The Journal of Korea Robotics Society
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• v.11 no.1
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• pp.1-8
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• 2016

In this paper, we propose a new algorithm of the guidance line extraction for autonomous agricultural robot based on vision camera in paddy field. It is the important process for guidance line extraction which finds the central point or area of rice row. We are trying to use the central region data of crop that the direction of rice leaves have convergence to central area of rice row in order to improve accuracy of the guidance line. The guidance line is extracted from the intersection points of extended virtual lines using the modified robust regression. The extended virtual lines are represented as the extended line from each segmented straight line created on the edges of the rice plants in the image using the Hough transform. We also have verified an accuracy of the proposed algorithm by experiments in the real wet paddy.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.749-754
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• 2021

In order to solve problems such as a decrease in the agricultural population and an aging population, research on agricultural robots is being actively conducted for the purpose of automating various agricultural tasks. The harvesting process is the most labor-intensive process among farm work and this process consumes about 2-3 times more compared to other processes. Since the transport of agricultural crops requires the most labor costs and there is a risk of injury during the operation, automating the transport operation through an agricultural robot can improve safety and significantly improve productivity. Therefore, this paper proposes an agricultural robot that is optimized for farm worksites and capable of autonomous driving.

• Korean Journal of Agricultural Science
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• v.49 no.4
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• pp.785-793
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• 2022

In this study, tomato maturity was estimated based on deep learning for a harvesting robot. Tomato images were obtained using a RGB camera installed on a monitoring robot, which was developed previously, and the samples were cropped to 128 × 128 size images to generate a dataset for training the classification model. The classification model was constructed based on convolutional neural networks, and the mean-variance loss was used to learn implicitly the distribution of the data features by class. In the test stage, the tomato maturity was estimated as a continuous index, which has a range of 0 to 1, by calculating the expected class value. The results show that the F1-score of the classification was approximately 0.94, and the performance was similar to that of a deep learning-based classification task in the agriculture field. In addition, it was possible to estimate the distribution in each maturity stage. From the results, it was found that our approach can not only classify the discrete maturation stages of the tomatoes but also can estimate the continuous maturity.

• Journal of Drive and Control
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• v.19 no.2
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• pp.1-10
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• 2022

Field robots operate in various areas, including construction, agriculture, forestry and manufacturing. Typical tasks of field robots used in various areas include excavation, flattening, and demolition. Such tasks are often accomplished in narrow alleys or indoors. In the case of field robots, there is a limit to working in a small space. Thus, to compensate for these shortcomings, many field robots equipped with Tiltrotators have recently been observed. The advantages of Tiltrotator are improved task efficiency and reduced operating time by reducing unnecessary behavior. We need simulation models that can improve the ability of new people to work and simulate tasks in advance. Thus, in this paper, we developed a simscape-based simulation model and modeling of 6DOF systems for field robots equipped with Tiltrotator. Dynamic modeling of field robot 3D models using Simcape multibody and hydraulic systems of field robots using Simcape Hydraulics were modeled. We applied a PID controller to create a control system that operates along the input angle. Simulation results show that errors occur when comparing input and output angles, but overall, they move along input angles.

• Journal of the Semiconductor & Display Technology
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• v.17 no.3
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• pp.65-69
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• 2018

In this paper, we have developed a multi-attitude monitoring system for running farm robots for field farming. There are many agricultural robots that can select work modules for various tasks. In order to control the stable attitude of agricultural robots connected to each other, we developed a system for monitoring the roll angle and pitch angle difference by fusing the information of the attitude monitoring system mounted on the robot mainframe and the work module. The developed attitude monitoring system showed resolution below 1 degree. In this paper, roll angle difference of 20 degrees and 60 degrees is measured with a multi - attitude monitoring system.