• 자동차안전학회지
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• 제12권2호
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• pp.33-39
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• 2020

This paper presents an Around View Monitoring (AVM) stop-line detection based longitudinal position correction algorithm for automated driving on urban roads. Poor positioning accuracy of low-cost GPS has many problems for precise path tracking. Therefore, this study aims to improve the longitudinal positioning accuracy of low-cost GPS. The algorithm has three main processes. The first process is a stop-line detection. In this process, the stop-line is detected using Hough Transform from the AVM camera. The second process is a map matching. In the map matching process, to find the corrected vehicle position, the detected line is matched to the stop-line of the HD map using the Iterative Closest Point (ICP) method. Third, longitudinal position of low-cost GPS is updated using a corrected vehicle position with Kalman Filter. The proposed algorithm is implemented in the Robot Operating System (ROS) environment and verified on the actual urban road driving data. Compared to low-cost GPS only, Test results show the longitudinal localization performance was improved.

• Journal of Positioning, Navigation, and Timing
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• 제10권4호
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• pp.243-251
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• 2021

Real-Time Kinematic (RTK) is a phase-based differential GNSS technique and uses additional observations from permanent reference stations to mitigate or eliminate effects like atmospheric delays or satellite clocks and orbit errors. In particular, as the position accuracy required in the fields of autonomous vehicles and drones is gradually increasing, the demand for RTK-based precise navigation that can provide cm-level position is increasing. Recently, with the rapid growth of the open-source software market, the use of open-source software for building navigation system of unmanned vehicles, which is difficult to mount an expensive GNSS receivers, is gradually increasing. RTKLIB is an open-source software package that can perform RTK positioning and is widely used for research and education purposes. However, since the performance and stability of RTK algorithm of RTKLIB is inevitably inferior to that of commercial GNSS receivers, users need to verify whether RTKLIB can satisfy the navigation performance requirements of unmanned vehicles. Therefore, in this paper, the performance evaluation of the RTK positioning algorithm of RTKLIB was performed using GNSS observation data acquired in a dynamic environment. Therefore, in this paper, the RTK positioning performance of RTKLIB was evaluated using GNSS observation data acquired in a dynamic environment. Our results show that the current RTK algorithm of RTKLIB is not suitable for precise navigation of unmanned vehicles.

• Journal of Astronomy and Space Sciences
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• 제18권1호
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• pp.63-70
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• 2001

IDGPS(Inverted Differential Global Positioning System)는 GPS의 위치 결정 정밀도를 향상시키는 여러 기법들 중 하나로서 주로 차량 위치 추적이나 물류 시스템에 이용된다. 본 연구에 적용된 IDGPS 기법은 사용자측에서 보내준 GPS 위치해와 위성정보, 그리고 기준국에서 생성된 오차 보정 정보를 이용해 관제국에서 사용자의 위치를 보정하는 것이다. 기준국과 사용자에서 발생한 오차들의 공간적 비상관성(spatial decorrelation)으로 인해 생길 수 있는 정밀도 보정 효과의 저하를 여러 개의 기준국을 이용한 NIDGPS(Network IDGPS)를 통해 해결하였다. 차량항법용 수신기를 사용자 수신기로서 사용하여 실험한 결과, IDGPS와 NIDGPS를 통해 단독 측위에 비해 평균적으로 2배 이상 정밀도가 향상됨을 확인할 수 있었다.

• Journal of Positioning, Navigation, and Timing
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• 제7권3호
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• pp.113-125
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• 2018

Since the global positioning system receivers on the surface of the Earth use satellite signals sent from a remote distance and the intensity of received signals is weak, they are vulnerable to jamming. This paper implements a vector-tracking loop (VTL)-based global navigation satellite system (GNSS) receiver algorithm as an anti-jamming technique and compares the performance of VTL-based receivers with that of scalar-tracking loop (STL) that is used in general GNSS receivers at various jamming environments and a vehicle's dynamics. The simulation results shows that VTL is more robust against jamming than STL in all operating environments.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.418-421
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• 2001

Press brake is used as bending and forming sheet metal in vehicle and many kind of industry. This paper deals with development of NC press brake based on high precision positioning device and software, which can be operated on personal computer. In this system, positioning device is used for controlling bending angle and operated by the developed software, which is database from material property, width and thickness of material. This study will make distribution in development of computer aided press brake.

• 로봇학회논문지
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• 제11권4호
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• pp.217-225
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• 2016

Dynamic Positioning (DP) is used to automatically maintain the position and heading of a floating structure subjected to environmental disturbances. A DP control system is composed of a motion controller to compute the desired force and moment and a thrust allocator to distribute the computed force and moment to multiple thrusters considering mechanical and operational constraints. Among various thruster configurations, azimuth thrusters or propeller/rudder pairs tend to make the allocation problem difficult to solve, because these types of propulsion systems include nonlinear constraints. In this paper, a dynamic positioning strategy for a twin-thruster ship that is propelled by two azimuthing thrusters is addressed, and a thrust allocation method which does not require a numerical optimization solver is proposed. The applicability of the proposed method is demonstrated with an experiment using an autonomous boat.

• 한국ITS학회 논문지
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• 제14권3호
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• pp.9-23
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• 2015

차로변경은 운전자의 숙련된 주변인식 및 운전기술이 요구되어 심각한 교통사고를 야기한다. 그리하여 우리는 불가피한 차로변경이 대두되는 고속도로 합류구간에서 본선으로 합류하는 차량의 차로변경을 보조하는 차량 자동제어 시스템 (ALCAS; Advanced Lane Change Assist System)을 개발한다. 본 연구에서는 ALCAS 중 조향이 수행되기 이전에 최적 차로변경 시작지점(Optimal Lane Change Start Point; OLCSP)을 생성하고 그 지점까지 도달하는 종방향 제어 알고리즘 개발에 초점을 두었다. 이를 위해 우선 고속도로 합류구간의 차로변경 행태를 분석하였고, 실제 차량의 가속도 함수 형태를 통해 차로변경 특징모형(Lane Change Feature Model)을 설계하였다. 그 후 차로변경 수행 단계를 정립하였으며, 이 알고리즘 성능과 타당성을 검증하기 위하여 다양한 주변차량 주행환경에 따른 시나리오 시험을 수행하였다. 또한 개발된 알고리즘의 효과를 미시적 교통류 시뮬레이션 (VISSIM)을 통해 확인하였다. 개발한 알고리즘을 합류차량에 적용한 결과 안정류 상태에서 합류성능이 두드러지게 개선되는 것을 확인하였다. 이 차량 자동제어 시스템은 교통 자동차 분야 융합기술의 일환으로 개발되었으며, 운전자의 부하와 오류를 감소시켜 효율성과 안전성을 향상시킬 뿐만 아니라 교통류의 안정성, 임계용량, 주행 효율성의 증대로 사회비용 감소를 기대할 수 있다.

• 한국항행학회논문지
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• 제14권5호
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• pp.648-654
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• 2010

본 논문에서는 위성항법 기반의 위치 정보를 이용하여 주행하는 AGV(Autonomous Guided Vehicle)의 안전성을 향상시키기 위한 항법 시스템을 구성하고 성능 시험을 수행하였다. 이를 위해 위성항법 신호에 급격한 오차를 감지하고 위성항법 신호가 단절된 경우에도 연속적인 주행이 가능하도록 DR(Dead Reckoning) 항법 시스템을 구성하였다. 주행 시험 결과 0.15m이상의 위성항법 오차를 감지할 수 있었으며 8초의 위성항법 신호 단절에서 약 1.5m 이내의 오차로 안정적인 주행을 확인할 수 있었다.

• Journal of Positioning, Navigation, and Timing
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• 제6권4호
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• pp.159-166
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• 2017

The position of autonomous driving vehicle is basically acquired through the global positioning system (GPS). However, GPS signals cannot be received in tunnels. Due to this limitation, localization of autonomous driving vehicles can be made through sensors mounted on them. In particular, a 3D Light Detection and Ranging (LIDAR) system is used for longitudinal position error correction. Few feature points and structures that can be used for localization of vehicles are available in tunnels. Since lanes in the road are normally marked by solid line, it cannot be used to recognize a longitudinal position. In addition, only a small number of structures that are separated from the tunnel walls such as sign boards or jet fans are available. Thus, it is necessary to extract usable information from tunnels to recognize a longitudinal position. In this paper, fire hydrants and evacuation guide lights attached at both sides of tunnel walls were used to recognize a longitudinal position. These structures have highly distinctive reflectivity from the surrounding walls, which can be distinguished using LIDAR reflectivity data. Furthermore, reflectivity information of tunnel walls was fused with the road surface reflectivity map to generate a synthetic reflectivity map. When the synthetic reflectivity map was used, localization of vehicles was able through correlation matching with the local maps generated from the current LIDAR data. The experiments were conducted at an expressway including Maseong Tunnel (approximately 1.5 km long). The experiment results showed that the root mean square (RMS) position errors in lateral and longitudinal directions were 0.19 m and 0.35 m, respectively, exhibiting precise localization accuracy.

• 반도체디스플레이기술학회지
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• 제17권1호
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• pp.88-92
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• 2018

Currently drone industry has become one of the fast growing markets and the technology for unmanned aerial vehicles are expected to continue to develop at a rapid rate. Especially small unmanned aerial vehicle systems have been designed and utilized for the various field with their own specific purposes. In these fields the path planning problem to find the shortest path between two oriented points is important. In this paper we introduce a path planning strategy for an autonomous flight of unmanned aerial vehicles through reinforcement learning with self-positioning technique. We perform Q-learning algorithm, a kind of reinforcement learning algorithm. At the same time, multi sensors of acceleraion sensor, gyro sensor, and magnetic are used to estimate the position. For the functional evaluation, the proposed method was simulated with virtual UAV environment and visualized the results. The flight history was based on a PX4 based drones system equipped with a smartphone.