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국내 최대 정보 기계·건설 공학연구정보센터
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  • 실험실 소개

    한국과학기술원 Mobile Robotics & Intelligence Laboratoryhome

    실험실 소개 이미지
    실험실 정보안내
    지도교수 김진환
    전공분류 로봇공학(Robotics),
    주소 대전광역시 유성구 대학로 291 3105,N27 Building, OSE, KAIST
    전화 042-350-1519
    홈페이지 http://orin.kaist.ac.kr/

    실험실소개

     

      The Ocean Robotics & Intelligence Lab is a research group focused on dynamic analysis and intelligent control of marine vehicles and robotic systems. We are conducting research on vehicle dynamics, guidance, control and estimation for various applications in the area of ocean engineering. We are also focusing on developing and implementing innovative algorithms and systems using robotics and artificial intelligence techniques, which are applicable to marine vehicles and autonomous robot systems.

     

     

    Mobile Robotics & Intelligence Laboratory (MORIN Lab) is a research group focused on intelligent control and autonomy of vehicles and mobile robotic systems. We are conducting research on dynamics, guidance, control and estimation across the full range of manned and unmanned vehicle applications . We are also working on developing innovative algorithms and techniques which are applicable to all types of vehicles and mobile robotic systems.

     

    연구분야

     

    Image processing
    3D Reconstruction of an underwater environment
    Path planning
    Analytical criteria for collision avoidance
    Path planning using machine learning
    Hydrodynamic analysis
    Hydrodynamic Analysis of Fish Locomotion
    Object Recognition
    Vision-based obstacle detection & recognition
    Dynamics & Control
    Dynamic positioning of an underactuated vehicle
    Navigation
    Navigation using weld lines
    Underwater Navigation using Sensor fusion

    연구성과

    Kim, J, Tandale, Monish, Menon, P. K.
    Modeling Air-Traffic Service Time Uncertainties for Queuing Network Analysis
    IEEE Transactions on Aerospace and Electronic Systems, 2012, Vol. 48, No. 0, pp. 525~ 541

    Kim, J., Vaddi, S. S., Menon, P. K. and Ohlmeyer E. J
    Comparison between Nonlinear Filtering Techniques for Spiraling Ballistic Missile State Estimation
    IEEE Transactions on Aerospace and Electronic Systems, 2012, Vol. 48, No. 0, pp. 313~ 328

    Kim, J. and Kim, T.
    Terrain-Based Localization using Particle Filter for Underwater Navigation
    International Journal of Ocean Engineering, 2011, Vol. 0, No. 0, pp. 0~ 0

    Kim, J., Tandale, M., Menon, P. K. and Ohlmeyer, E
    Particle Filter for Ballistic Target Tracking with Glint Noise
    AIAA Journal of Guidance, Control and Dynamics, 2010, Vol. 33, No. 6, pp. 1918~ 1921

    Kim, J., Palaniappan, K., and Menon, P. K.
    Rapid Estimation of Impaired Aircraft Aerodynamic Parameters
    AIAA Journal of Aircraft, 2010, Vol. 47, No. 4, pp. 1216~ 1228

    Jungwook Han, Yonghoon Cho and Jinwhan Kim
    Coastal SLAM with Marine Radar for USV Operation in GPS-Restricted Situation
    IEEE Journal of Oceanic Engineering, 2018, Vol. 0, No. 0, pp. 0~ 0

    Byunghyun Yoo and Jinwhan Kim
    Probabilistic modeling of ship powering performance using full-scale operational data
    Applied Ocean Research, 2019, Vol. 82, No. 0, pp. 1~ 9

    Seonghun Hong and Jinwhan Kim
    Selective image registration for efficient visual SLAM on planar surface structures in underwater environment
    Autonomous Robots, 2019, Vol. 0, No. 0, pp. 0~ 0

    Jungwook Han, Jinwhan Kim and David Hyunchul Shim
    Precise localization and mapping in indoor parking structures via parameterized SLAM
    IEEE Transactions on Intelligent Transportation Systems, 2018, Vol. 0, No. 0, pp. 0~ 0

    프로젝트

    [Dynamic modeling and simulation for an underwater mine killer robot] Hydrodynamic coeffiencts are estimated by semi analytical / empirical method using specification of robot

    [Localization and Navigation in a Time-Invariant Non-Uniform Scalar Field] This project is to develop an algorithm for localization and navigation using a series of point measurements in a time-invariant non-uniform scalar field whose distribution is known.

    [AUV Navigation using Sensor fusion] The performance of a sensor is decreasing and available sensors are limited in underwater and therefore sensor fusion is necessary to improve performance.

    [Developed multi-purpose intelligent unmmaned surface vehicle] Development of image processing technique considering sensor fusion with vision image and motion sensor

    [Development of a global path planning algorithm for AUV] Path planning considering obstacle and complex current field maps

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