• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 1996.06c
• /
• pp.802-811
• /
• 1996

Farmers need alternatives for weed control due to the desire to reduce chemicals used in farming. However, conventional mechanical cultivation cannot selectively remove weeds located in the seedline between crop plants and there are no selective heribicides for some crop/weed situations. Since hand labor is costly , an automated weed control system could be feasible. A robotic weed control system can also reduce or eliminate the need for chemicals. Currently no such system exists for removing weeds located in the seedline between crop plants. The goal of this project is to build a real-time , machine vision weed control system that can detect crop and weed locations. remove weeds and thin crop plants. In order to accomplish this objective , a real-time robotic system was developed to identify and locate outdoor plants using machine vision technology, pattern recognition techniques, knowledge-based decision theory, and robotics. The prototype weed control system is composed f a real-time computer vision system, a uniform illumination device, and a precision chemical application system. The prototype system is mounted on the UC Davis Robotic Cultivator , which finds the center of the seedline of crop plants. Field tests showed that the robotic spraying system correctly targeted simulated weeds (metal coins of 2.54 cm diameter) with an average error of 0.78 cm and the standard deviation of 0.62cm.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2000.11c
• /
• pp.722-728
• /
• 2000

This study of field control machine in the recycled vinyl rail is gantry crane type and promoting agricultural automatization through self-controlled spraying, harvesting and conveyance. In addition to, that control machine could get a cost and labor reduction effect through automatization and make better environment by preventing farmers from agrichemical damage, accidents and recycling wasted vinyl. That machine is able to be divided as traveling, spraying, harvesting and conveyance sections. In driving section consists of girder frame, carrier, rail, control system, driving system, working machine, rail and loading device for working machine. This machine has following advantages to be able to bring a big innovation in the agricultural industry. I) Accurate performance is able to be done by proper positioning due to based on the rails. 2) The soil is not made hard like heavy tractor 3) The wheel is not sank into the soil and slipped well under rain like heavy tractor. Therefore, weather and soil situation could not affect working condition. 4) Complete unmanned control and 24hours-working are available due to traveling on the rails. 5) It could use various energy resources like not only liquid fuel but also solar, common electronic power due to traveling on the rails.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.12 no.3
• /
• pp.201-210
• /
• 2019

This paper proposes the AMCS(Agricultural Machine Control System that distinguishes farms using satellite photos or drone photos of farms and controls the self-driving and operation of farm drones and tractors. The AMCS consists of the LSM(Local Server Module) which separates farm boundaries from sensor data and video image of drones and tractors, reads remote control commands from the main server, and then delivers remote control commands within the management area through the link with drones and tractor sprinklers and the PSM that sets a path for drones and tractors to move from the farm to the farm and to handle work at low cost and high efficiency inside the farm. As a result of AMCS performance analysis proposed in this paper, the PSM showed a performance improvement of about 100% over Dijkstra algorithm when setting the path from external starting point to the farm and a higher working efficiency about 13% than the existing path when setting the path inside the farm. Therefore, the PSM can control tractors and drones more efficiently than conventional methods.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.10 no.6
• /
• pp.39-45
• /
• 2011

Due to the introduction of the electronic control systems, agricultural machine is getting complicated with its special function. The complex electronics system increases difficulty of maintenances in the wiring harness system. The heavy wiring harness has some poor reliability and workability in the production line of manufacture also. So, in this study, some small local control modules are developed to complement the difficulties with the benefits of distributed control system. All of the local control modules are connected by using CAN communication. This system developed this study has the advantages of modification or alteration of wiring and local modules. All the sensors and actuators can be easily monitored and controlled by the main controller with the appropriate communication protocol made by in this study.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 1993.10a
• /
• pp.810-819
• /
• 1993

An autonomous lan vehicle for agriculture(ALVA-II) was developed. A prototype vehicle was made by modifying a commercial tractor. A Navigation sensor system with a geo-magnetic sensor performed the autonomous operations of ALVA-II, such as rotary tilling with headland turnings. A navigation sensor system with a machine vision system was also investigated to control ALVA-II following a work boudnary.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2000.11b
• /
• pp.354-362
• /
• 2000

In Korea, researches on year-round leaf vegetables production system are in progress, most of them focused on environmental control. Therefore, automation technologies for harvesting, transporting, and grading are in great demand. A robot system for harvesting lettuces, composed of a 3-DOF (degree of freedom) manipulator, an end-effector, a lettuce feeding conveyor, an air blower, a machine vision system, six photoelectric sensors, and a fuzzy logic controller, was developed. A fuzzy logic control was applied to determine appropriate grip force on lettuce. Leaf area index and height were used as input variables and voltage as an output variable for the fuzzy logic controller. Success rate of the lettuce harvesting was 94.12%, and average harvesting time was approximately 5 seconds per lettuce.

• Agricultural and Biosystems Engineering
• /
• v.4 no.1
• /
• pp.16-21
• /
• 2003

In the agricultural field, a machine vision system has been widely used to automate most inspection processes especially in quality grading. Though machine vision system was very effective in quantifying geometrical quality factors, it had a deficiency in quantifying color information. This study was conducted to evaluate color of beef using machine vision system. Though measuring color of a beef using machine vision system had an advantage of covering whole lean tissue area at a time compared to a colorimeter, it revealed the problem of sensitivity depending on the system components such as types of camera, lighting conditions, and so on. The effect of color balancing control of a camera was investigated and multi-layer BP neural network based color calibration process was developed. Color calibration network model was trained using reference color patches and showed the high correlation with L*a*b* coordinates of a colorimeter. The proposed calibration process showed the successful adaptability to various measurement environments such as different types of cameras and light sources. Compared results with the proposed calibration process and MLR based calibration were also presented. Color calibration network was also successfully applied to measure the color of the beef. However, it was suggested that reflectance properties of reference materials for calibration and test materials should be considered to achieve more accurate color measurement.

• Journal of Biosystems Engineering
• /
• v.32 no.3
• /
• pp.179-189
• /
• 2007

Most of the seeds of cucurbitaceous rootstock species used for grafting were mainly sown by hand. This study was carried out to develop an on-line discriminating algorithm of seed direction using machine vision and an automatic seeding system. The seeding system was composed of a supplying device, feeding device, machine vision system, reversing device, seeding device and system control section. Machine vision was composed of a color CCD camera, frame grabber, image inspection chamber, lighting and personal computer. The seed image was segmented into a region of seed part and background part using thresholding technique in which H value of HSI color coordinate system. A seed direction was discriminated by comparing position between the center of circumscribed rectangle to a seed and the center of seed image. It took about 49ms to identify and redirect seed. Line-up status of seed was good the more than 95% of a sowed seed. Seeding capacity of this system was shown to be 10,140 grains per hour, which is three times faster than that of a typical worker.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 1998.12a
• /
• pp.208-215
• /
• 1998

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 1993.10a
• /
• pp.768-778
• /
• 1993

The system is designed for the production and processing of feed, fertilizer, sugar , and grain. It can be used to weigh and transport automatically their pellet, power or nonstickness materials. In this system, we use discontinuous totalising automatic weighing instruments to weigh materials. It is a closed-cycle control system controlled by industrial controlling computer STD bus. The system used for processing grain and feed can improve the quality of products , carry out scientific management, increase productivity and decrease the intensity of labour