• Journal of Drive and Control
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• v.20 no.3
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• pp.35-41
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• 2023

Radish and Chinese cabbage are the most produced and consumed vegetables in Korea. The mechanization of harvesting operations is necessary to minimize the need for manual labor. This study to develop and evaluate the performance of a multi-purpose driving platform that can apply modular Radish and Chinese cabbage harvesting devices. The multi-purpose driving platform consisted of driving, device control, engine, hydraulic, harvesting, conveying, and loading part. Radish and Chinese cabbage harvesting conducted using the multi-purpose driving platform each harvesting module. The performance of the multi-purpose driving platform was evaluated the field efficiency and loss rate. The total Radish harvesting operation time 34.3 min., including 28.8 min., of harvesting time, 1.9 min., of turning time, and 3.6 min., of replacement time of bulk bag. During Radish harvesting, the field efficiency and average loss rate of the multi-purpose driving platform were 2.0 hr/10a and 3.1 %. Chinese cabbage harvesting operation 49.3 min., including 26.6 min., of harvesting time, 4.6 min., of turning time, and 18.1 min., of replacement time of bulk bag. During Chinese cabbage harvesting, the field efficiency and average loss rate of the multi-purpose driving platform 2.1 hr/10a and 0.1 %. Performance evaluation of the multi-purpose driving platform that harvesting work was possible by installing Radish and Chinese cabbage harvest modules. Performance analysis through harvest performance evaluation in various Radish and Chinese cabbage cultivation environments is necessary.

• The Journal of Korea Robotics Society
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• v.16 no.4
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• pp.319-326
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• 2021

To improve the driving performance and work efficiency of the multi-purpose agricultural robot, this paper conducted a study on the turning and steering characteristics of the robot platform according to the characteristics of the working machine coupled to the multi-purpose agricultural robot considering the agricultural environment. First, the size and characteristics of the developed multi-purpose agricultural robot platform and working machine, and the targeted field farming work environment are analyzed. And based on this analysis, the problems that arise in multi-purpose robots with conventional turning methods are quantitatively presented. And to overcome this problem, an improved turning and steering method for multi-purpose agricultural robots is proposed considering the characteristics of various workstations and the agricultural working environment. Finally, by applying the proposed method, the turning characteristics of the multi-purpose agricultural robot according to the working machine are analyzed and the effectiveness of the proposed method is verified.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.1-8
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• 2023

In this paper, we propose a black ice detection platform framework using Convolutional Neural Networks (CNNs). To overcome black ice problem, we introduce a real-time based early warning platform using CNN-based architecture, and furthermore, in order to enhance the accuracy of black ice detection, we apply a multi-scale dilation convolution feature fusion (MsDC-FF) technique. Then, we establish a specialized experimental platform by using a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Experimental results of a real-time black ice detection platform show the better performance of our proposed network model compared to conventional image segmentation models. Our proposed platform have achieved real-time segmentation of road black ice areas by deploying a road black ice area segmentation network on the edge device Jetson Nano devices. This approach in parallel using multi-scale dilated convolutions with different dilation rates had faster segmentation speeds due to its smaller model parameters. The proposed MsCD-FF Net(2) model had the fastest segmentation speed at 5.53 frame per second (FPS). Thereby encouraging safe driving for motorists and providing decision support for road surface management in the road traffic monitoring department.

• Korean Journal of Agricultural Science
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• v.51 no.2
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• pp.133-146
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• 2024

Selection of gear reduction ratio is essential for machine design to ensure suitable power and speed during agricultural operations. The goal of the study was to evaluate the gear reduction ratio for a 1.6 kW four-wheel-drive (4WD) multi-purpose agricultural electric vehicle platform using workload data under different off-road conditions. A data acquisition system was fabricated to collect workload (torque) of the vehicle acting on the gear shaft. Field tests were performed under three driving surfaces (asphalt, concrete, and grassland), payload operations (981, 2,942, and 4,903 N), and slope conditions (0 - 4°, 4 - 8°, and 8 - 12°), respectively. Commercial speed reduction gear phases were attached to the input shaft of the vehicle powertrain. The maximum required torque was recorded as 37.5 Nm at a 4,903 N load with 8 - 12° slope levels, and the minimum torque was 12.32 Nm at 0 - 4° slope levels with a 981 Nm load for a 4 km/h speed on asphalt, concrete, and grassland roads. Based on the operating load condition and motor torque and rotational speed (TN) curve, the minimum and maximum gear reduction ratios were chosen as 1 : 50 and 1 : 64, respectively. The selected motor satisfied power requirements by meeting all working torque criteria with the gear reduction ratios. The chosen motor with a gear reduction ratio of 1 : 50 was suitable to fit with the motor T-N curve, and produced the maximum speeds and loads needed for driving and off-road activities. The findings of the study would assist in choosing a suitable gear reduction ratio for electric vehicle multi-purpose field operations.

• Journal of Institute of Convergence Technology
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• v.13 no.1
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• pp.19-22
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• 2023

The rise of electrification and the advancement of autonomous driving technologies are leading to new forms of mobility, such as serving and delivery robots. However, due to factors such as the small-scale production of various products and the high cost of autonomous driving sensors, product prices have risen, limiting accessibility to consumers. To improve this, we developed a multi-purpose mobility platform that is mass-producible, based on inexpensive, reliable sensors and a configurable human tracking system. As a result, the unit price is approximately 50% of the launch prices of other mobility products, and additional cost savings are possible through component optimization in the future. In addition, more added value will be created through the distribution of integrated mobility platforms that can be combined with various usable modules to meet a variety of user needs, such as cargo transportation, wheelchair power kits, and mobile monitors.

• Journal of the Korea Society for Simulation
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• v.29 no.3
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• pp.19-25
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• 2020

The field farming machine is difficult to develop due to its heavy slopes, tough roads and unformatted cultivation by growing crops. In particular, harvesting is a major problem in rural areas in Republic of Korea where aging is accelerated with work requiring a lot of time and manpower. This study seeks to analyze the dynamic characteristics of hot pepper harvester developed to replace manpower, reduce working hours and mechanize harvesting operations. To analyze the dynamic characteristics of a hot pepper harvester, the dynamic program Recurdyn was used and all analysis were performed as case of an empty vehicle. Based on the results, this study can suggest dynamic safety range of multi-purpose driving platform with hot pepper harvester.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.283-290
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• 2007

A bi-modal tram has been developed to offer an advanced transportation service compared with existing vehicles. The All-Wheel-Steering system is applied to the bi-modal tram to satisfy the required steering performance because the bi-modal tram has extended length and articulated mechanism. An ECU for the steering system is essential to steer wheels on 2nd and 3rd axles by the specific AWS algorithm with the prescribed driving condition. The Hardware-In-the-Loop Simulation(HILS) system is planned for the purpose of evaluating the steering system of the bi-modal tram. There are kinematic links with the hydraulic actuator to steer wheels on each 2nd and 3rd axles and also same steering mechanism as the actual vehicle is in the HILS system. Controlling the movement of hydraulic actuator which reflects the lateral steering reaction force on each wheel is the key to realize the HILS system, but the reaction force is continuously changed according to various driving conditions. Therefore, the simulation through the multi-body dynamics model is used to obtain the required forces.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.250-256
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• 2014

EV(Electric Vehicle) has many benefits such as prevention of global warming and so on. But due to driving source changing from combustion engine to battery and e-motor, new R&D difficulties have arisen which changing of desired vehicle performance and multidisciplinary design constraints by means of strong coupled multi-physics domain problems. Additionally, dynamics performances of EV becomes more important due to increasing customer's demands and expectations for EV in compare with internal combustion engine vehicle. In this paper suggests model based development platform of EV through integrated simulation environment for improving analyse & design accuracy in order to solve multi-physics problem. This simulation environment is integrated by three following specialized simulation tools IPG CarMaker, AVL Cruise, DYMOLA that adapted to each purpose. Furthermore, control algorithm of TV(Torque Vectoring) system is developed using independent driven e-motor at rear wheels for improving handling performance of EV. TV control algorithm and its improved vehicle performances are evaluated by numerical simulation from standard test methods.