• Title/Summary/Keyword: vehicle positioning technology

검색결과 143건 처리시간 0.026초

Development of an Autonomous Navigation System for Unmanned Ground Vehicle

  • Kim, Yoon-Gu;Lee, Ki-Dong
    • 대한임베디드공학회논문지
    • /
    • 제3권4호
    • /
    • pp.244-250
    • /
    • 2008
  • This paper describes the design and implementation of an unmanned ground vehicle (UGV) and also estimates how well autonomous navigation and remote control of UGV can be performed through the optimized arbitration of several sensor data, which are acquired from vision, obstacle detection, positioning system, etc. For the autonomous navigation, lane detection and tracing, global positioning, and obstacle avoidance are necessarily required. In addition, for the remote control, two types of experimental environments are established. One is to use a commercial racing wheel module, and the other is to use a haptic device that is useful for a user application based on virtual reality. Experimental results show that autonomous navigation and remote control of the designed UGV can be achieved with more effectiveness and accuracy using the proper arbitration of sensor data and navigation plan.

  • PDF

GPS와 INS의 센서융합을 이용한 확장형 칼만필터 설계 및 자율항법용 회피알고리즘 개발 (Avoidance Algorithm and Extended Kalman Filter Design for Autonomous Navigation with GPS & INS Sensor System Fusion)

  • 유환신
    • 한국항행학회논문지
    • /
    • 제11권2호
    • /
    • pp.146-153
    • /
    • 2007
  • 무인자동차는 스스로 목적지와 경유지를 찾아서 항행할 수 있는 이동체이다. 이러한 항행의 성능을 보다 정밀하게 향상시키기 위하여 본 논문에서는 관성항법과 GPS를 융합한 확장형 칼만필터를 적용한 보정 알고리즘을 개발하였다. 확장형 칼만필터의 성능을 검증하기 위하여 무인자동차의 실차실험을 실시하고 그 결과로서 필터의 효율성을 확인하였다.

  • PDF

Design of Trajectory Generator for Performance Evaluation of Navigation Systems

  • Jae Hoon Son;Sang Heon Oh;Dong-Hwan Hwang
    • Journal of Positioning, Navigation, and Timing
    • /
    • 제12권4호
    • /
    • pp.409-421
    • /
    • 2023
  • In order to develop navigation systems, simulators that provide navigation sensors data are required. A trajectory generator that simulates vehicle motion is needed to generate navigation sensors data in the simulator. In this paper, a trajectory generator for evaluating navigation system performance is proposed. The proposed trajectory generator consists of two parts. The first part obtains parameters from the motion scenario file whereas the second part generates position, velocity, and attitude from the parameters. In the proposed trajectory generator six degrees of freedom, halt, climb, turn, accel turn, spiral, combined, and waypoint motions are given as basic motions with parameters. These motions can be combined to generate complex trajectories of the vehicle. Maximum acceleration and jerk for linear motion and maximum angular acceleration and velocity for rotational motion are considered to generate trajectories. In order to show the usefulness of the proposed trajectory generator, trajectories were generated from motion scenario files and the results were observed. The results show that the proposed trajectory generator can accurately simulate complex vehicle motions that can be used to evaluate navigation system performance.

A Positioning DB Generation Algorithm Applying Generative Adversarial Learning Method of Wireless Communication Signals

  • Ji, Myungin;Jeon, Juil;Cho, Youngsu
    • Journal of Positioning, Navigation, and Timing
    • /
    • 제9권3호
    • /
    • pp.151-156
    • /
    • 2020
  • A technology for calculating the position of a device is very important for users who receive positioning services, regardless of various indoor/outdoor or with/without any positioning infrastructure existence environments. One of the positioning resources widely used at present, LTE, is a typical infrastructure that can overcome the space limitation, however its positioning method based on the position of the LTE base station has low accuracy. A method of constructing a radio wave map of an LTE signal has been proposed as a method for overcoming the accuracy, but it takes a lot of time and cost to perform high-density collection in a wide area. In this paper, we describe a method of creating a high-density DB for the entire region by using vehicle-based partial collection data. To create a positioning database, we applied the idea of Generative Adversarial Network (GAN), which has recently been in the spotlight in the field of deep learning, and learned the collected data. Then, a virtually generated map which having the smallest error from the actual data is selected as the optimum DB. We verified the effectiveness of the positioning DB generation algorithm using the positioning data obtained from un-collected area.

플로어 마크를 이용한 차량용 실내 정밀 측위 기술 (Indoor Precise Positioning Technology for Vehicles Using Floor Marks)

  • 박지훈;이재성
    • 한국정보통신학회논문지
    • /
    • 제19권10호
    • /
    • pp.2321-2330
    • /
    • 2015
  • 실내에서 무용지물이 되는 GPS 의 한계로 다양한 실내 측위 기술에 대한 연구가 진행되고 있으나 대부분 사설 무선 네트워크 기반의 실내 측위 방법들로 고가의 설치 및 유지보수 비용, 비실시간성, 그리고 낮은 정확도 때문에 상용화가 어려운 실정이다. 본 논문에서는 기존에 증강현실에 사용되던 마크 인식 알고리즘을 최초로 차량용 실내 측위분야에 적용하였다. 지면에 플로어 마크를 설치하고 마크의 투영 변환 및 정보 디코딩을 통해 마크 내부의 정보(절대 좌표)를 인식하고 기하학적 분석을 통해 차량이 마크로부터 떨어진 정밀한 위치와 접근 방향(상대 좌표)를 인지할 수 있도록 하였다. 실험 결과 5m 단위로 마크를 설치했을 때 약 30 cm 이내의 오차만 발생하였고, 20km/h 의 속도에서 초당 20 프레임의 이미지 중 43.2% 의 마크 인식률을 보여 충분히 상용화 가치가 있음을 확인하였다.

A Fusion Positioning System of Long Baseline and Pressure Sensor for Ship and Harbor Inspection ROV

  • Seo, Dong-Cheol;Lee, Yong-Hee;Jo, Gyung-Nam;Choi, Hang-Shoon
    • Journal of Ship and Ocean Technology
    • /
    • 제11권1호
    • /
    • pp.36-46
    • /
    • 2007
  • The maintenance of a ship is essential for safe navigation and hence regular surveys are prescribed according to the rule of classification societies. A hull inspection is generally performed by professional divers, but it takes a long time and the efficiency is low in terms of time and cost. In this research, a ROV(Remotely Operated Vehicle) named as SNU-ROV(Seoul National University-ROV) is developed to replace the conventional inspection method. In this system, the ROV is intended to be used for inspecting ship and harbor because harbor inspection is merging as a safety measure against any possible terror actions. In order to increase the efficiency of inspection, the ROV must be able to measure the exact position of damages. SNU-ROV has a positioning system based on LBL(Long Base Line). In shallow water such as harbor, however, LBL has bad DOP(Dilution of Precision) in the depth direction due to the limited depth. Thus LBL only can not locate the exact depth position. To solve the DOP problem, a pressure sensor is introduced to LBL and a complementary filter is attached by using indirect feedback Kalman filter. Thus developed positioning system is verified by simulation and experiment in towing tank.

A Study on Compact Network RTK for Land Vehicles and Real-Time Test Results

  • Song, Junesol;Park, Byungwoon;Kee, Changdon
    • Journal of Positioning, Navigation, and Timing
    • /
    • 제7권1호
    • /
    • pp.43-52
    • /
    • 2018
  • In recent years, the need of high accuracy navigation for vehicles has increased due to the development of autonomous driving vehicles and increase in land transportation convenience. This study is performed for vehicle users to achieve a performance of centimeter-level positioning accuracy by utilizing Compact Network Real-time Kinematic (RTK) that is applicable as a national-level infrastructure. To this end, medium-baseline RTK was implemented in real time to estimate accurate integer ambiguities between reference stations for reliable generation of Network RTK correction using the linear combination of carrier-phase observations and L1/L2 pseudo-range measurements. The residual tropospheric error was estimated in real time to improve the accuracy of double-differenced integer ambiguity resolution between network configuration reference stations that have at least 30 km or longer baseline distance. In addition, C++ based software was developed to enable real-time generation and broadcasting of Compact Network RTK correction information by utilizing an accurately estimated double-differenced integer ambiguity values. As a result, the horizontal and vertical 95% accuracy was 2.5cm and 5.2cm, respectively, without performance degradation due to user's position change within the network.

비전 기반 측위 보조 알고리즘의 성능 분석 (Performance Analysis of Vision-based Positioning Assistance Algorithm)

  • 박종수;이용;권재현
    • 한국측량학회지
    • /
    • 제37권3호
    • /
    • pp.101-108
    • /
    • 2019
  • 최근 컴퓨터 처리 속도의 향상과 영상 처리 기술의 발달로 인해 카메라에서 획득하는 정보를 기존의 GNSS(Global Navigation Satellite System), 추측 항법 기반의 측위 기술과 결합하여 안정적인 위치를 결정하기 위한 연구가 활발히 진행 중이다. 기존 연구에서는 단안 카메라를 이용한 연구가 주로 수행되었으나 이 경우 관심 객체의 절대좌표가 구축이 되어 있어야 한다는 한계점이 있다. 이러한 한계를 극복하기 위해 본 연구에서는 스테레오 영상으로부터 삼각측량법을 적용하여 카메라와 관심 객체간 거리를 추정하는 비전 기반 측위 보조 알고리즘을 개발하고 성능 분석을 수행하였다. 또한, 추정된 거리와 카메라 영상 획득 간격을 이용해 상대적인 속도를 계산하고 이를 기존에 개발된 GNSS/이동체 내부 센서 기반 측위 알고리즘과 결합하여 통합 측위 알고리즘을 구현하였다. 실제 주행 자료를 기반으로 통합측위 알고리즘에 대한 성능을 분석한 결과 기존에 개발된 GNSS/이동체 내부 센서 기반 측위 알고리즘에 비해 속도 정보를 항법해 보정에 활용하였을 때 약 4%의 미미한 위치 정확도 향상 효과를 확인하였다. 이는 영상으로부터 추정된 속도 정보의 정밀도가 낮고, 터널 등을 지날 때는 영상으로부터 적절한 정보를 추출할 수 없다는 한계가 있어 이를 보완한 추가 연구가 필요하다고 판단된다.

포텐셜 필드 기법을 이용한 무인차량의 자율항법 개발 (Navigation Technique of Unmanned Vehicle Using Potential Field Method)

  • 이상원;문영근;김성현;이민철
    • 한국자동차공학회논문집
    • /
    • 제19권4호
    • /
    • pp.8-15
    • /
    • 2011
  • This paper proposes a real-time navigation algorithm which integrates the artificial potential field (APF) for an unmanned vehicle in the unknown environment. This approach uses repulsive potential function around the obstacles to force the vehicle away and an attractive potential function around the goal to attract the vehicle. In this research, laser range finder is used as range sensor. An obstacle detected by the sensor creates repulsive vector. Differential global positioning system (DGPS) and digital compass are used to measure the current vehicle position and orientation. The measured vehicle position is also used to create attractive vector. This paper proposes a new concept of potential field based navigation which controls unmanned vehicle's speed and steering. The magnitude of repulsive force based on the proposed algorithm is designed not to be over the magnitude of attractive force while the magnitude is increased linearly as being closer to obstacle. Consequently, the vehicle experiences a generalized force toward the negative gradient of the total potential. This force drives the vehicle downhill towards its goal configuration until the vehicle reaches minimum potential and it stops. The effectiveness of the proposed APF for unmanned vehicle is verified through simulation and experiment.

INS/GNSS/NHC Integrated Navigation System Compensating for Lever Arm Effect between NHC Effective Point and IMU Mounting Location

  • Chae, Myeong Seok;Kwon, Jae Uk;Cho, Eui Yeon;Cho, Seong Yun
    • Journal of Positioning, Navigation, and Timing
    • /
    • 제11권3호
    • /
    • pp.199-208
    • /
    • 2022
  • Inertial Navigation System (INS)/Global Navigation Satellite System (GNSS) integrated navigation system can be used for land vehicle navigation. When the GNSS signal is blocked in a dense urban area or tunnel, however, the problem of increasing the error over time is unavoidable because navigation must be performed only with the INS. In this paper, Non-Holonomic Constraints (NHC) information is utilized to solve this problem. The NHC may correct some of the errors of the INS. However, it should be noted that NHC information is not applicable to all areas within the vehicle. In other words, the lever arm effect occurs according to the distance between the Inertial Measurement Unit (IMU) mounting position and the NHC effective point, which causes the NHC condition not to be satisfied at the IMU mounting position. In this paper, an INS/GNSS/NHC integrated navigation filter is designed, and this filter has a function to compensate for the lever arm effect. Therefore, NHC information can be safely used regardless of the vehicle's driving environment. The performance of the proposed technology is verified through Monte-Carlo simulation, and the performance is confirmed through experimental test.