• Journal of Biosystems Engineering
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• v.23 no.2
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• pp.179-186
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• 1998

This study was conducted to sense posture of an autonomous tractor using a DGPS, a gyro compass, and a potentiometer. Posture sensing system was constructed and its accuracy was evaluated. The accuracy of DGPS was evaluated under stationary and moving conditions, and the performance of the gyro compass and the potentiometer was investigated by measuring bearing and steering angles, respectively. Also, the effect of DGPS interference by obstacles was evaluated experimentally. The position accuracy was about 6.6cm(95%) under the stationary condition and 10 cm at sharp turning condition. Steering angle of the tractor could be related linearly to the output of the potentiometer that was installed on the rotating center of a knuckle arm. The positioning accuracy of the DGPS varied significantly according to the number of visible GPS satellites, but was good with more than 7 satellites. The DGPS gave bad solutions for sensing the posture of tractor when signals from satellites or the correction data from the base were interfered by obstacles.

• Journal of Sensor Science and Technology
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• v.16 no.4
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• pp.294-300
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• 2007

Autonomous unmanned vehicle is able to find the path and the way point by itself. For the more precise navigation performance, Extended kalman filter, which is integrated with inertial navigation system and global positioning system is proposed in this paper. Extended kalman filter's performance is evaluated by the simulation and applied to the unmanned vehicle. The test result shows the effectiveness of extended kalman filter for the navigation.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.164-167
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• 2017

자율주행자동차는 운전자의 개입 없이 스스로 목적지까지 도착할 수 있는 차량으로 세계 여러나라의 자동차 업체 뿐만 아니라 IT분야에서도 개발중에 있다. 일반 자동차와는 달리 차량에 카메라와 GPS, 각종 센서 등 IT 기술들이 도입되어 운전자와 차량 간에 소통이 이루어지면서 편리함을 가져다 준다. 그러나 자율주행자동차는 하나의 스마트폰이 탑재되었다고 볼 수 있을 만큼 지능적이고 다양한 기술이 적용되어 있기 때문에 취약점과 위협 요소가 존재한다. 본 논문에서는 자율주행자동차의 운행으로 인해 야기될 수 있는 취약점을 분석하고 적용 가능한 보안 고려사항을 제시한다.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.480-487
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• 2009

Autonomous Lane detection with vision is a difficult problem because of various road conditions, such as shadowy road surface, various light conditions, and the signs on the road. In this paper we propose a robust lane detection algorithm to overcome shadowy road problem using a statistical method. The algorithm is applied to the vision-based mobile robot system and the robot followed the lane with the lane following controller. In parallel with the lane following controller, the global position of the robot is estimated by the developed localization method to specify the locations where the lane is discontinued. The results of experiments, done in the region where the GPS measurement is unreliable, show good performance to detect and to follow the lane in complex conditions with shades, water marks, and so on.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.2
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• pp.95-100
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• 2013

Localization is very important for the autonomous navigation of Unmanned Ground Vehicles; however, it is difficult that they have a precise Inertial Navigation System(INS) sensor, especially Small Unmanned Ground Vehicle(SUGV). Moreover, there are some condition such as denial of global position system(GPS), GPS/INS integrated system is not robust. This paper proposes the estimation algorithm with optical flow sensor and INS. Being compared with previous researches, the proposed algorithm is suitable for skid steering vehicles. We revised the measurement model of previous research for the accuracy of side direction position. Experimental results were performed to verify the algorithm, and the result showed an excellent performance.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.1
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• pp.1-10
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• 2015

In urban area, since multipath and signal attenuations frequently occur due to street trees, street lights and buildings, it is difficult to obtain accurate navigation solution using GPS. As these problems also impact negatively on the INS/GPS coupled system, implementing advanced transportation systems such as autonomous navigation system and Intelligent Transportation System (ITS) become quite hard. For this reason, to alleviate deterioration of navigation system performance in urban area, direction information extraction algorithm using vision system is proposed in this paper. 2D Finite Rate of Innovation (FRI) technique is applied to extract lane edges. The proposed technique is simulated using road images and feasibility of proposed technique is analyzed through the simulation results.

• Electronics and Telecommunications Trends
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• v.36 no.4
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• pp.61-71
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• 2021

Navigation satellite systems (GPS, GLONASS etc.) provide three main services, i.e., positioning for location based services, navigation for multi-modal transportation services, and timing for communication and critical infrastructure services. They were started as military systems but were extended to civil service. Navigation satellite navigation system began with GPS in the USA and GLONASS in Russia at nearly the same time. Indian NavIC and Chines BDS announced their FOCs in 2016 and 2020, respectively and European Galileo and Japanese QZSS are catching up others. In these days, Navigation Satellite System, Positioning, Navigation, and Timing services are part of our daily life very closely. They are required for autonomous driving car, Unmanned vehicles like UAV, UGV, and UMV, 5G/6G telecommunications, world financial system, power system, survey, agriculture, and so on. The services among navigation satellite systems are very competitive and also cooperative one another. This article describes the status of these systems and evolution in the technical and service senses, which may be helpful for planning korea positioning system(KPS).

• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.378-387
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• 2007

In this paper, Authors develop and verify the algorithm for enhancing the performance of Unmanned vehicle's Autonomous navigation, and also propose the method of establishing much more precise Navigation locus. Unmanned vehicle has a destination, however orientation is not notified, which make it find the future orientation itself. Extended Kalman Filter make it access to the desirable direction, which coupled with INS and GPS is proposed in this paper. Sliding mode control could overcome the side slip and lateral minor movement of the vehicle. The test result would shows the effectiveness of Extended kalman filter and Slide mode control for the navigation.

• Journal of Auto-vehicle Safety Association
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• v.9 no.2
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• pp.6-12
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• 2017

An autonomous driving system based on a precise digital map is developed. The system is implemented to the Hyundai's Tucsan fuel cell car, which has a camera, smart cruise control (SCC) and Blind spot detection (BSD) radars, 4-Layer LiDARs, and a standard GPS module. The precise digital map has various information such as lanes, speed bumps, crosswalks and land marks, etc. They can be distinguished as lane-level. The system fuses sensed data around the vehicle for localization and estimates the vehicle's location in the precise map. Objects around the vehicle are detected by the sensor fusion system. Collision threat assessment is performed by detecting dangerous vehicles on the precise map. When an obstacle is on the driving path, the system estimates time to collision and slow down the speed. The vehicle has driven autonomously in the Hyundai-Kia Namyang Research Center.

• The Journal of Korea Robotics Society
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• v.15 no.1
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• pp.16-23
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• 2020

This paper describes an alignment algorithm that estimates the initial heading angle of AUVs (Autonomous Underwater Vehicle) for starting navigation in a sea area. In the basic dead reckoning system, the initial orientation of the vehicle is very important. In particular, the initial heading value is an essential factor in determining the performance of the entire navigation system. However, the heading angle of AUVs cannot be measured accurately because the DCS (Digital Compass) corrupted by surrounding magnetic field in pointing true north direction of the absolute global coordinate system (not the same to magnetic north direction). Therefore, we constructed an experimental constraint and designed an algorithm based on extended Kalman filter using only inertial navigation sensors and a GPS (Global Positioning System) receiver basically. The value of sensor covariance was selected by comparing the navigation results with the reference data. The proposed filter estimates the initial heading angle of AUVs for navigation in a sea area and reflects sampling characteristics of each sensor. Finally, we verify the performance of the filter through experiments.