• Title/Summary/Keyword: Inertial navigation system

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Implementation of Pattern Recognition Algorithm Using Line Scan Camera for Recognition of Path and Location of AGV (무인운반차(AGV)의 주행경로 및 위치인식을 위한 라인스캔카메라를 이용한 패턴인식 알고리즘 구현)

  • Kim, Soo Hyun;Lee, Hyung Gyu
    • Journal of Korea Society of Industrial Information Systems
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    • v.23 no.1
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    • pp.13-21
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    • 2018
  • AGVS (Automated Guided Vehicle System) is a core technology of logistics automation which automatically moves specific objects or goods within a certain work space. Conventional AGVS generally requires the in-door localization system and each AGV equips expensive sensors such as laser, magnetic, inertial sensors for the route recognition and automatic navigation. thus the high installation cost is inevitable and there are many restrictions on route(path) modification or expansion. To address this issue, in this paper, we propose a cost-effective and scalable AGV based on a light-weight pattern recognition technique. The proposed pattern recognition technology not only enables autonomous driving by recognizing the route(path), but also provides a technique for figuring out the loc ation of AGV itself by recognizing the simple patterns(bar-code like) installed on the route. This significantly reduces the cost of implementing AGVS as well as benefiting from route modification and expansion. In order to verify the effectiveness of the proposed technique, we first implement a pattern recognition algorithm on a light-weight MCU(Micro Control Unit), and then verify the results by implementing an MCU_controlled AGV prototype.

Development of Underwater Positioning System using Asynchronous Sensors Fusion for Underwater Construction Structures (비동기식 센서 융합을 이용한 수중 구조물 부착형 수중 위치 인식 시스템 개발)

  • Oh, Ji-Youn;Shin, Changjoo;Baek, Seungjae;Jang, In Sung;Jeong, Sang Ki;Seo, Jungmin;Lee, Hwajun;Choi, Jae Ho;Won, Sung Gyu
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.3
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    • pp.352-361
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    • 2021
  • An underwater positioning method that can be applied to structures for underwater construction is being developed at the Korea Institute of Ocean Science and Technology. The method uses an extended Kalman filter (EKF) based on an inertial navigation system for precise and continuous position estimation. The observation matrix was configured to be variable in order to apply asynchronous measured sensor data in the correction step of the EKF. A Doppler velocity logger (DVL) can acquire signals only when attached to the bottom of an underwater structure, and it is difficult to install and recover. Therefore, a complex sensor device for underwater structure attachment was developed without a DVL in consideration of an underwater construction environment, installation location, system operation convenience, etc.. Its performance was verified through a water tank test. The results are the measured underwater position using an ultra-short baseline, the estimated position using only a position vector, and the estimated position using position/velocity vectors. The results were compared and evaluated using the circular error probability (CEP). As a result, the CEP of the USBL alone was 0.02 m, the CEP of the position estimation with only the position vector corrected was 3.76 m, and the CEP of the position estimation with the position and velocity vectors corrected was 0.06 m. Through this research, it was confirmed that stable underwater positioning can be carried out using asynchronous sensors without a DVL.