• Title/Summary/Keyword: Precision Navigation

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A Comparative Analysis of Performance of Ambiguity Validation Methods (미지정수 후보 타당성 검정 기법간의 비교 분석)

  • Ko, Jae-Young;Shin, Mi-Young;Han, Young-Hoon;Cho, Deuk-Jae
    • Journal of Navigation and Port Research
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    • v.39 no.1
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    • pp.15-21
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    • 2015
  • In high precision positioning systems based on GNSS, ambiguity resolution is an important procedure. Correct ambiguity leads to positioning results which have high precision between millimeters and centimeters. However, when the ambiguity is determined incorrectly, ensuring accuracy and precision of the positioning result is impossible. An ambiguity validation test is required to obtain correct ambiguity when ambiguity resolution is performed based on the ILS (Integer Least Squares), which shows the best performance in point of theory and experiment when compared with other methods such as IR (Integer Rounding) and IB (Integer Bootstrapping). Comparison between the candidates of the validation test is needed to judge ambiguity correctly, because ILS searches for candidates of integer ambiguity, unlike other methods which calculate only one integer ambiguity. We analyzed the experimental performance of ambiguity validation tests. R-ratio, F-ratio and W-ratio were adopted for analysis. The performance of validation tests was evaluated by classifying normal operation, detection, missed detection and false alarm. As a result, strengths and weaknesses of validation tests was showed to experimental. we concluded that validation tests must be selected according to environment.

Correction in the Measurement Error of Water Depth Caused by the Effect of Seafloor Slope on Peak Timing of Airborne LiDAR Waveforms (지형 기울기에 의한 항공 수심 라이다 수심 측정 오차 보정)

  • Sim, Ki Hyeon;Woo, Jae Heun;Lee, Jae Yong;Kim, Jae Wan
    • Journal of the Korean Society for Precision Engineering
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    • v.34 no.3
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    • pp.191-197
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    • 2017
  • Light detection and ranging (LiDAR) is one of the most efficient technologies to obtain the topographic and bathymetric map of coastal zones, superior to other technologies, such as sound navigation and ranging (SONAR) and synthetic aperture radar (SAR). However, the measurement results using LiDAR are vulnerable to environmental factors. To achieve a correspondence between the acquired LiDAR data and reality, error sources must be considered, such as the water surface slope, water turbidity, and seafloor slope. Based on the knowledge of those factors' effects, error corrections can be applied. We concentrated on the effect of the seafloor slope on LiDAR waveforms while restricting other error sources. A simulation regarding in-water beam scattering was conducted, followed by an investigation of the correlation between the seafloor slope and peak timing of return waveforms. As a result, an equation was derived to correct the depth error caused by the seafloor slope.

Autonomous Tracking Control of Intelligent Vehicle using GPS Information (GPS 정보를 이용한 지능형 차량의 자율 경로추적 제어)

  • Chung, Byeung-Mook;Seok, Jin-Woo;Cho, Che-Seung;Lee, Jae-Won
    • Journal of the Korean Society for Precision Engineering
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    • v.25 no.10
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    • pp.58-66
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    • 2008
  • In the development of intelligent vehicles, path tracking of unmanned vehicle is a basis of autonomous driving and automatic navigation. It is very important to find the exact position of a vehicle for the path tracking, and it is possible to get the position information from GPS. However the information of GPS is not the current position but the past position because a vehicle is moving and GPS has a time delay. In this paper, therefore, the moving distance of a vehicle is estimated using a direction sensor and a velocity sensor to compensate the position error of GPS. In the steering control, optimal fuzzy rules for the path tracking can be found through the simulation of Simulink. Real driving experiments show the fuzzy rules are good for the steering control and the position error of GPS is well compensated by the proposed estimation method.

Self-localization for Mobile Robot Navigation using an Active Omni-directional Range Sensor (전방향 능동 거리 센서를 이용한 이동로봇의 자기 위치 추정)

  • Joung, In-Soo;Cho, Hyung-Suck
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.1 s.94
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    • pp.253-264
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    • 1999
  • Most autonomous mobile robots view only things in front of them, and as a result, they may collide with objects moving from the side or behind. To overcome this problem. an Active Omni-directional Range Sensor System has been built that can obtain an omni-directional range data through the use of a laser conic plane and a conic mirror. Also, mobile robot has to know its current location and heading angle by itself as accurately as possible to successfully navigate in real environments. To achieve this capability, we propose a self-localization algorithm of a mobile robot using an active omni-directional range sensor in an unknown environment. The proposed algorithm estimates the current position and head angle of a mobile robot by a registration of the range data obtained at two positions, current and previous. To show the effectiveness of the proposed algorithm, a series of simulations was conducted and the results show that the proposed algorithm is very efficient, and can be utilized for self-localization of a mobile robot in an unknown environment.

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Traveling Performance of a Robot Platform for Unmanned Weeding in a Dry Field (벼농사용 무인 제초로봇의 건답환경 주행 성능)

  • Kim, Gook-Hwan;Kim, Sang-Cheol;Hong, Young-Ki
    • Journal of the Korean Society for Precision Engineering
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    • v.31 no.1
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    • pp.43-50
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    • 2014
  • This paper introduces a robot platform which can do weeding while traveling between rice seedlings stably against irregular land surface of a paddy field. Also, an autonomous navigation technique that can track on stable state without any damage of the seedlings in the working area is proposed. Detection of the rice seedlings and avoidance knocking down by the robot platform is achieved by the sensor fusion of a laser range finder (LRF) and an inertial measurement unit (IMU). These sensors are also used to control navigating direction of the robot to keep going along the column of rice seedling consistently. Deviation of the robot direction from the rice column that is sensed by the LRF is fed back to a proportional and derivative controller to obtain stable adjustment of navigating direction and get proper returning speed of the robot to the rice column.

A Study on the Path-Tracking of Electric Wheelchair Robot (전동휠체어 로봇의 경로추적제어에 관한 연구)

  • Ahn, Kyoung-Kwan;Yoon, Jong-Il;Le, Duy Khoa
    • Journal of the Korean Society for Precision Engineering
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    • v.28 no.11
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    • pp.1265-1271
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    • 2011
  • These days the number of aged and disabled people is increasing rapidly. But most of the disabled or the aged who have the ability to work, want to engage in economic activities and solve social restrictions as well as their bad financial conditions. This paper concerns about the tracking control of an electric wheelchair robot for welfare vehicle where the seat and electric wheelchair are separated and electric wheelchair robot must be autonomously controlled without the help of assistant. So the aged or the disabled people can drive welfare vehicle by himself by adopting this system. Therefore the concept of both an autonomous driving of electric wheelchair and path tracking robots is required in this system. Finally we suggested fuzzy controller in order to control the path tracking of electric wheelchair robot and compared the capability of the proposed controller with conventional PID controller.

Lateral Control of Vision-Based Autonomous Vehicle using Neural Network (신형회로망을 이용한 비젼기반 자율주행차량의 횡방향제어)

  • 김영주;이경백;김영배
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2000.11a
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    • pp.687-690
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    • 2000
  • Lately, many studies have been progressed for the protection human's lives and property as holding in check accidents happened by human's carelessness or mistakes. One part of these is the development of an autonomouse vehicle. General control method of vision-based autonomous vehicle system is to determine the navigation direction by analyzing lane images from a camera, and to navigate using proper control algorithm. In this paper, characteristic points are abstracted from lane images using lane recognition algorithm with sobel operator. And then the vehicle is controlled using two proposed auto-steering algorithms. Two steering control algorithms are introduced in this paper. First method is to use the geometric relation of a camera. After transforming from an image coordinate to a vehicle coordinate, a steering angle is calculated using Ackermann angle. Second one is using a neural network algorithm. It doesn't need to use the geometric relation of a camera and is easy to apply a steering algorithm. In addition, It is a nearest algorithm for the driving style of human driver. Proposed controller is a multilayer neural network using Levenberg-Marquardt backpropagation learning algorithm which was estimated much better than other methods, i.e. Conjugate Gradient or Gradient Decent ones.

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Laser Image SLAM based on Image Matching for Navigation of a Mobile Robot (이동 로봇 주행을 위한 이미지 매칭에 기반한 레이저 영상 SLAM)

  • Choi, Yun Won;Kim, Kyung Dong;Choi, Jung Won;Lee, Suk Gyu
    • Journal of the Korean Society for Precision Engineering
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    • v.30 no.2
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    • pp.177-184
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    • 2013
  • This paper proposes an enhanced Simultaneous Localization and Mapping (SLAM) algorithm based on matching laser image and Extended Kalman Filter (EKF). In general, laser information is one of the most efficient data for localization of mobile robots and is more accurate than encoder data. For localization of a mobile robot, moving distance information of a robot is often obtained by encoders and distance information from the robot to landmarks is estimated by various sensors. Though encoder has high resolution, it is difficult to estimate current position of a robot precisely because of encoder error caused by slip and backlash of wheels. In this paper, the position and angle of the robot are estimated by comparing laser images obtained from laser scanner with high accuracy. In addition, Speeded Up Robust Features (SURF) is used for extracting feature points at previous laser image and current laser image by comparing feature points. As a result, the moving distance and heading angle are obtained based on information of available points. The experimental results using the proposed laser slam algorithm show effectiveness for the SLAM of robot.

Autonomous Traveling of Unmanned Golf-Car using GPS and Vision system (GPS와 비전시스템을 이용한 무인 골프카의 자율주행)

  • Jung, Byeong Mook;Yeo, In-Joo;Cho, Che-Seung
    • Journal of the Korean Society for Precision Engineering
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    • v.26 no.6
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    • pp.74-80
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    • 2009
  • Path tracking of unmanned vehicle is a basis of autonomous driving and navigation. For the path tracking, it is very important to find the exact position of a vehicle. GPS is used to get the position of vehicle and a direction sensor and a velocity sensor is used to compensate the position error of GPS. To detect path lines in a road image, the bird's eye view transform is employed, which makes it easy to design a lateral control algorithm simply than from the perspective view of image. Because the driving speed of vehicle should be decreased at a curved lane and crossroads, so we suggest the speed control algorithm used GPS and image data. The control algorithm is simulated and experimented from the basis of expert driver's knowledge data. In the experiments, the results show that bird's eye view transform are good for the steering control and a speed control algorithm also shows a stability in real driving.

DOP Analysis of Ground Based Augmentation System by the Position of Transmitter (송신기 위치에 따른 GBAS 시스템의 DOP 분석)

  • Lim, Joong-Soo;Chae, Gyoo-Soo
    • Journal of Satellite, Information and Communications
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    • v.8 no.1
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    • pp.40-44
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    • 2013
  • In this paper, we describe on the position error of GBAS. In reality, there are many sources which make errors into the calculation of receiver position. It is well known that the DOP of GBAS is an important position error source and is dependent on the numbers and positions of the transmitters. Here, we develop an algorism to calculate the DOP of the GNSS with 2-line transmitters into Korean area. The result is useful to predict the DOP of the positions where transmitters and receivers are located.