• Title/Summary/Keyword: dead reckoning position

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Underwater Localization using RF Sensor and INS for Unmanned Underwater Vehicles (RF 센서와 INS을 이용한 UUV 위치 추정)

  • Park, Daegil;Kwak, Kyungmin;Jung, Jaehoon;Kim, Jinhyun;Chung, Wan Kyun
    • Journal of Ocean Engineering and Technology
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    • v.31 no.2
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    • pp.170-176
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    • 2017
  • In this paper, we propose an underwater localization scheme through the fusion of an inertial navigation system (INS) and the received signal strength (RSS) of electromagnetic (EM) wave sensors to guarantee precise localization performance with high sampling rates. In this localization scheme, the INS predicts the pose of the unmanned underwater vehicle (UUV) by dead reckoning at every step, and the RF sensors corrects the UUV position functions using the Earth-fixed reference when the UUV is located in underwater wireless sensor networks (UWSN). The localization scheme and state modeling were conducted in the extended Kalman filter framework, and UUV localization experiments were conducted in a basin environment. The scheme achieved reliable localization accuracy during long-term navigation, demonstrating the feasibility of exploiting EM wave attenuation as Earth-fixed reference sensors.

Localization Algorithm for Lunar Rover using IMU Sensor and Vision System (IMU 센서와 비전 시스템을 활용한 달 탐사 로버의 위치추정 알고리즘)

  • Kang, Hosun;An, Jongwoo;Lim, Hyunsoo;Hwang, Seulwoo;Cheon, Yuyeong;Kim, Eunhan;Lee, Jangmyung
    • The Journal of Korea Robotics Society
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    • v.14 no.1
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    • pp.65-73
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    • 2019
  • In this paper, we propose an algorithm that estimates the location of lunar rover using IMU and vision system instead of the dead-reckoning method using IMU and encoder, which is difficult to estimate the exact distance due to the accumulated error and slip. First, in the lunar environment, magnetic fields are not uniform, unlike the Earth, so only acceleration and gyro sensor data were used for the localization. These data were applied to extended kalman filter to estimate Roll, Pitch, Yaw Euler angles of the exploration rover. Also, the lunar module has special color which can not be seen in the lunar environment. Therefore, the lunar module were correctly recognized by applying the HSV color filter to the stereo image taken by lunar rover. Then, the distance between the exploration rover and the lunar module was estimated through SIFT feature point matching algorithm and geometry. Finally, the estimated Euler angles and distances were used to estimate the current position of the rover from the lunar module. The performance of the proposed algorithm was been compared to the conventional algorithm to show the superiority of the proposed algorithm.

Evaluation of the Use of Inertial Navigation Systems to Improve the Accuracy of Object Navigation

  • Iasechko, Maksym;Shelukhin, Oleksandr;Maranov, Alexandr;Lukianenko, Serhii;Basarab, Oleksandr;Hutchenko, Oleh
    • International Journal of Computer Science & Network Security
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    • v.21 no.3
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    • pp.71-75
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    • 2021
  • The article discusses the dead reckoning of the traveled path based on the analysis of the video data stream coming from the optoelectronic surveillance devices; the use of relief data makes it possible to partially compensate for the shortcomings of the first method. Using the overlap of the photo-video data stream, the terrain is restored. Comparison with a digital terrain model allows the location of the aircraft to be determined; the use of digital images of the terrain also allows you to determine the coordinates of the location and orientation by comparing the current view information. This method provides high accuracy in determining the absolute coordinates even in the absence of relief. It also allows you to find the absolute position of the camera, even when its approximate coordinates are not known at all.

Adaptive Sensor/Heterogeneous Infrastructure Integrated Pedestrian Navigation Technology using Rényi Divergence-based Outlier Detection (Rényi Divergence 기반 이상치 검출을 통한 적응형 센서/이종 인프라 통합 보행자 항법 기술)

  • Jae Uk Kwon;Seong Yun Cho;JaeJun Yoo;SeongHun Seo
    • Journal of Positioning, Navigation, and Timing
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    • v.13 no.3
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    • pp.289-299
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    • 2024
  • In the Pedestrian Dead Reckoning (PDR)/Global Positioning System (GPS)/Wi-Fi-integrated navigation system for indoor/outdoor continuous positioning of pedestrians, the process of detecting outliers in measurements is very important. When accurate location information from measurements is used, reliable correction data can be generated during the fusion filtering process. However, abnormal measurements may occur in certain situations, such as indoor/outdoor transitions, which can degrade filter performance and lead to significant errors in the estimated position. To address this issue, this paper proposes a method for detecting outliers in measurements based on Rényi Divergence (RD). When the deviation of the RD value is large, the measurements are considered outliers, and positioning is performed using only pure PDR. Based on experiments conducted with real data, it was confirmed that outliers were effectively detected for abnormal measurements, leading to an improvement in the performance of pedestrian navigation.

A Study on Precision Positioning Methods for Autonomous Mobile Robots Using VRS Network-RTK GNSS Module (VRS 네트워크-RTK GNSS 모듈을 이용한 자율 이동 로봇의 정밀 측위방법에 관한 연구)

  • Dong Eon Kim;YUN-JAE CHOUNG;Dong Seog Han
    • Journal of the Korean Association of Geographic Information Studies
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    • v.27 no.3
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    • pp.1-13
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    • 2024
  • This paper proposes a cost-effective system design and user-friendly approach for the key technological elements necessary to configure an autonomous mobile robot. To implement a high-precision positioning system using an autonomous mobile robot, we established a Linux-based VRS (virtual reference station)-RTK (real-time kinematic) GNSS (global navigation satellite system) system with NTRIP (Network Transport of RTCM via Internet Protocol) client functionality. Notably, we reduced the construction cost of the GNSS positioning system by performing dynamic location analysis of the established system, without utilizing an RTK replay system. Dynamic location analysis involves sampling each point during the trajectory following of the autonomous mobile robot and comparing the location precision with ground-truth points. The proposed system ensures high positioning performance with fast sampling times and suggests a GPS waypoint system for user convenience. The centimeter-level precision GNSS information is provided at a 30Hz sampling rate, and the dead reckoning function ensures valid information even when passing through tall buildings and dense forests. The horizontal position error measured through the proposed system is 6.7cm, demonstrating a highly precise dynamic location measurement error within 10cm. The VRS network-RTK Linux system, which provides precise dynamic location information at a high sampling rate, supports a GPS waypoint planner function for user convenience, enabling easy destination setting based on GPS information.

Mapping algorithm for Error Compensation of Indoor Localization System (실내 측위 시스템의 오차 보정을 위한 매핑 알고리즘)

  • Kim, Tae-Kyum;Cho, We-Duke
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.4
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    • pp.109-117
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    • 2010
  • With the advent of new technologies such as HSDPA, WiBro(Wireless Broadband) and personal devices, we can access various contents and services anytime and anywhere. A location based service(LBS) is essential for providing personalized services with individual location information in ubiquitous computing environment. In this paper, we propose mapping algorithm for error compensation of indoor localization system. Also we explain filter and indoor localization system. we have developed mapping algorithms composed of a map recognition method and a position compensation method. The map recognition method achieves physical space recognition and map element relation extraction. We improved the accuracy of position searching. In addition, we reduced position errors using a dynamic scale factor.

Development of an Autonomous Guide Robot for Campus Tour (캠퍼스 자율 안내로봇 개발)

  • Lim, Jong Hwan;Kim, Hee Jung
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.41 no.6
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    • pp.543-551
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    • 2017
  • A campus guide robot was developed that can autonomously guide people through a university campus. The robot is able to evaluate its location using Differential Global Positioning System (DGPS) and Dead-Reckoning using the encoders mounted on its wheels. The robot can navigate autonomously along a guide route that is set in advance. A new position-based guidance approach was suggested. Unlike the conventional method of setting the guide sequence in advance, the robot acquires guidance by judging whether there is guide information corresponding to its current position. The robot searches guide information from the guide database while it moves along the guide path autonomously. If there is any guide information available around the location of the robot, then it performs guide functions. We also suggested an effective guide scenario that can maximize the interest of people. The performance of the robot was tested through sets of experiments in a true campus environment.

Experiments of Unmanned Underwater Vehicle's 3 Degrees of Freedom Motion Applied the SLAM based on the Unscented Kalman Filter (무인 잠수정 3자유도 운동 실험에 대한 무향 칼만 필터 기반 SLAM기법 적용)

  • Hwang, A-Rom;Seong, Woo-Jae;Jun, Bong-Huan;Lee, Pan-Mook
    • Journal of Ocean Engineering and Technology
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    • v.23 no.2
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    • pp.58-68
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    • 2009
  • The increased use of unmanned underwater vehicles (UUV) has led to the development of alternative navigational methods that do not employ acoustic beacons and dead reckoning sensors. This paper describes a simultaneous localization and mapping (SLAM) scheme that uses range sonars mounted on a small UUV. A SLAM scheme is an alternative navigation method for measuring the environment through which the vehicle is passing and providing the relative position of the UUV. A technique for a SLAM algorithm that uses several ranging sonars is presented. This technique utilizes an unscented Kalman filter to estimate the locations of the UUV and surrounding objects. In order to work efficiently, the nearest neighbor standard filter is introduced as the data association algorithm in the SLAM for associating the stored targets returned by the sonar at each time step. The proposed SLAM algorithm was tested by experiments under various three degrees of freedom motion conditions. The results of these experiments showed that the proposed SLAM algorithm was capable of estimating the position of the UUV and the surrounding objects and demonstrated that the algorithm will perform well in various environments.

Localization on an Underwater Robot Using Monte Carlo Localization Algorithm (몬테카를로 위치추정 알고리즘을 이용한 수중로봇의 위치추정)

  • Kim, Tae-Gyun;Ko, Nak-Yong;Noh, Sung-Woo;Lee, Young-Pil
    • The Journal of the Korea institute of electronic communication sciences
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    • v.6 no.2
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    • pp.288-295
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    • 2011
  • The paper proposes a localization method of an underwater robot using Monte Carlo Localization(MCL) approach. Localization is one of the fundamental basics for autonomous navigation of an underwater robot. The proposed method resolves the problem of accumulation of position error which is fatal to dead reckoning method. It deals with uncertainty of the robot motion and uncertainty of sensor data in probabilistic approach. Especially, it can model the nonlinear motion transition and non Gaussian probabilistic sensor characteristics. In the paper, motion model is described using Euler angles to utilize the MCL algorithm for position estimation of an underwater robot. Motion model and sensor model are implemented and the performance of the proposed method is verified through simulation.

Research of MEMS INS Based 3D Positioning Technologies for Workers in Construction Field (MEMS INS 기반 건설현장작업자의 3D 위치결정기법에 관한 연구)

  • Jang, Yonggu;Kim, Hyunsoo;Do, Seungbok;Jeon, Heungsoo
    • Journal of the Korean GEO-environmental Society
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    • v.14 no.3
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    • pp.51-60
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    • 2013
  • It is proposed the new method to calculate the absolute altitude and horizontal position of worker in construction field. For this research, we used a pressure sensor, MEMS INS sensor to acquire 3D position of worker. The easiest way to show the result of this research is to use smart phone which equipped various digital sensors in this hardware. So we made two softwares: Data acquisition software in Android smart phone and Data monitoring software in PC. During this research, we encountered several kind of problems which have to be overcame. This paper shows these processes and the results of 3D positioning technologies we suggested newly.