• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.5
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• pp.551-557
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• 2014

This paper presents a robust lateral controller for autonomous guidance of a farm tractor in field operations. Although mechanical steering actuators have recently been used for passenger vehicles, the steering actuator of the farm tractor is based on a hydraulic system, resulting in limited bandwidth and a larger time delay. Based on a kinematic tractor model with steering actuator dynamics, a nonlinear control technique called dynamic surface control is applied to design a robust lateral controller that compensates for uncertainty owing to steering actuator and road geometry. Finally, tracking performance and robustness of the proposed controller are validated via commercial tractor simulations, with respect to the time delay of the steering actuator and road geometry (e.g., up and down hills), on a given field with a constant friction coefficient.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.308-316
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• 2004

As we know that there are so many restrictions controlling the autonomous robot to turn and move in an indoor space. In this research, Ive adopted the concept ‘Omni-directional wheel’ as a driving equipment, which makes it possible for the robot to move in horizontal and diagonal directions. Most of all, we eliminated the slip error problem, which can occur when the system generates power by means of slip. In order to solve this problem, we developed a ‘slip error correction algorithm’. Following this program, whenever the robot moves in any directions, it defines its course by comparing pre-programmed direction and the current moving way, which can be decided by extracted image of floor line. Additionally, this robot also provides the limited security and service function. It detects the motion of vehicle, transmits pictures to multiple users and can be moved by simple order's. In this paper, we tried to propose a practical model which can be used in an office.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.266-283
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• 2022

With the rapid development of autonomous vehicle technology, unexpected accidents are occurring. Therefore, it is necessary to minimize user accident damage through the development of autonomous traffic safety education. Since edge cases, accident type, and risk factor analysis are important for realistic education, overseas case studies and demonstrations were carried out, and based on this, two curriculum for service providers and general users were developed. The service provider curriculum consisted of OEDR, sudden stop, cut-in, take-over, defensive driving, system malfunction, policy and information security education, and the general user curriculum consisted of attention duty, take-over, operating design domain, accidents type, laws, functions, information security education.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.197-205
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• 2024

Development of AI and big data-based algorithms to advance and optimize the recognition and detection performance of various static/dynamic vehicles in front and around the vehicle at a time when securing driving safety is the most important point in the development and commercialization of autonomous vehicles. etc. are being studied. However, there are many research cases for recognizing the same vehicle by using the unique advantages of radar and camera, but deep learning image processing technology is not used, or only a short distance is detected as the same target due to radar performance problems. Therefore, there is a need for a convergence-based vehicle recognition method that configures a dataset that can be collected from radar equipment and camera equipment, calculates the error of the dataset, and recognizes it as the same target. In this paper, we aim to develop a technology that can link location information according to the installation location because data errors occur because it is judged as the same object depending on the installation location of the radar and CCTV (video).

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.10
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• pp.939-947
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• 2010

With the rising numbers of elderly and disabled people, the demand for welfare services using a robotic system and not involving human effort is likewise increasing. This study deals with a mobile-robot system combined with a BWS (Body Weight Support) system for gait rehabilitation. The BWS system is designed via the kinematic analysis of the robot's body-lifting characteristics and of the walking guide system that controls the total rehabilitation system integrated in the mobile robot. This mobile platform is operated by utilizing the AGV (Autonomous Guided Vehicle) driving algorithm. Especially, the method that integrates geometric path tracking and obstacle avoidance for a nonholonomic mobile robot is applied so that the system can be operated in an area where the elderly users are expected to be situated, such as in a public hospital or a rehabilitation center. The mobile robot follows the path by moving through the turning radius supplied by the pure-pursuit method which is one of the existing geometric path-tracking methods. The effectiveness of the proposed method is verified through the real experiments those are conducted for path tracking with static- and dynamic-obstacle avoidance. Finally, through the EMG (Electromyography) signal measurement of the subject, the performance of the proposed system in a real operation condition is evaluated.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.70-81
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• 2020

Point-by-point data, which is abundantly collected by vehicles with embedded GPS (Global Positioning System), generate useful information. These data facilitate decisions by transportation jurisdictions, and private vendors can monitor and investigate micro-scale driver behavior, traffic flow, and roadway movements. The information is applied to develop app-based route guidance and business models. Of these, speed data play a vital role in developing key parameters and applying agent-based information and services. Nevertheless, link speed values require different levels of physical storage and fidelity, depending on both collecting and reporting intervals. Given these circumstances, this study aimed to establish an appropriate collection interval to efficiently utilize Space Mean Speed information by vehicles with embedded GPS. We conducted a comparison of Probe-vehicle data and Image-based vehicle data to understand PE(Percentage Error). According to the study results, the PE of the Probe-vehicle data showed a 95% confidence level within an 8-second interval, which was chosen as the appropriate collection interval for Probe-vehicle data. It is our hope that the developed guidelines facilitate C-ITS, and autonomous driving service providers will use more reliable Space Mean Speed data to develop better related C-ITS and autonomous driving services.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.30-41
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• 2022

With the advent of autonomous driving, personal mobility, drones, and smart roads, it is necessary to respond to changes in the road traffic environment in the road guidance system. However, the use of road signs to guide the road is decreasing compared to the past due to the advent of devices such as navigation and smartphones. Therefore, in this study, a large-scale survey was conducted to derive road sign issues and usage plans to respond to future changes. Based on this, this study presented a strategy to diversify road sign functions by analyzing the factors affecting the use of road signs by citizens. As a result, first, it is necessary to provide real-time variable road guidance information that reflects user needs such as traffic, weather, and local events. Second, it is necessary to informatize digital road signs such as reflecting maps with precision. Third, it is necessary to demonstrate road guidance in a virtual environment that reflects various future mobility and road environments.

• Journal of Drive and Control
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• v.20 no.4
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• pp.27-34
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• 2023

Weeding in orchards is closely associated with productivity and quality. The customary weeding process is both labor-intensive and time-consuming. To solve the problems, there is need for automation of agricultural robots and machines in the agricultural field. On the other hand, orchards have complicated working areas due to narrow spaces between trees and amorphous terrain. Therefore, it is necessary to develop customized robot technology for unmanned weeding work within the department. This study developed a path generation and path control method for unmanned weeding according to the orchard environment. For this, the width of the weeding span, the number of operations, and the width of the weeding robot were used as input parameters for the orchard environment parameters. To generate a weeding path, a weeding robot was operated remotely to obtain GNSS-based location data along the superheated center line, and a driving performance test was performed based on the generated path. From the results of orchard field tests, the RMSE in weeding period sections was measured at 0.029 m, with a maximum error of 0.15 m. In the steering period within row and steering to the next row sections, the RMSE was 0.124 m, and 0.047 m, respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.62-73
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• 2022

As the competition among the autonomous vehicle (AV, here after) developers are getting fierce, Korean government has been supporting developers by deregulating safety standards and providing financial subsidies. Recently, some OEMs announced their plans to market Lv3 and Lv4 automated driving systems. However, these market changes raised concern among public road management sectors for monitoring road conditions and alleviating hazardous conditions for AVs and human drivers. In this regards, the authors proposed a methodology for monitoring road infrastructure to identify hazardous factors for AVs and categorizing the hazards based on their level of impact. To evaluate the degrees of the harm on AVs, the authors suggested a methodology for managing road hazard factors based on vehicle performance features including vehicle body, sensors, and algorithms. Furthermore, they proposed a method providing AVs and road management authorities with potential risk information on road by delivering them on the monitoring map with node and link structure.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.186-193
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• 2008

We propose a novel real-time obstacle avoidance method for rescue robots. This method, named the ELA(Emergency Level Around), permits the detection of unknown obstacles and avoids collisions while simultaneously steering the mobile robot toward safe position. In the ELA, we consider two sensor modules, PSD(Position Sensitive Detector) infrared sensors taking charge of obstacle detection in short distance and LMS(Laser Measurement System) in long distance respectively. Hence if a robot recognizes an obstacle ahead by PSD infrared sensors first, and judges impossibility to overcome the obstacle based on driving mode decision process, the order of priority is transferred to LMS which collects data of radial distance centered on the robot to avoid the confronted obstacle. After gathering radial information, the ELA algorithm estimates emergency level around a robot and generates a polar histogram based on the emergency level to judge where the optimal free space is. Finally, steering angle is determined to guarantee rotation to randomly direction as well as robot width for safe avoidance. Simulation results from wandering in closed local area which includes various obstacles and different conditions demonstrate the power of the ELA.