NAVIGATION OF AN AUTONOMOUS SURFACE VESSELUSING SIMULTANEOUS LOCALIZATION AND MAPPING WITHTHE EXTENDED KALMAN FILTER METHOD

  • سال انتشار: 1393
  • محل انتشار: یازدهمین همایش بین المللی سواحل، بنادر و سازه های دریایی
  • کد COI اختصاصی: ICOPMAS11_239
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 887
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نویسندگان

Ayoub Khodaparast

M.SC - Malek Ashtar University of Technology

Ali Jabar Rashidi

Assistant - Malek Ashtar University of Technology

Bahram Karimi

Assistant - Malek Ashtar University of Technology

Saeid MohammadHoseini

Assistant - Malek Ashtar University of Technology

چکیده

In this paper, Studied the navigation of an Autonomous Surface Vessel using SimultaneousLocalization and Mapping (SLAM). An autonomous surface vessel, the exploring environmentin which it is located by the interpretation of a scene. And only uses the information from thesensor can receive and interpret the information they need. The most common and safest sensorsused in navigation, the inertial navigation system. It is not affected by weather conditions,Jamming and identifiable. The disadvantage is that errors of the exponential increase over timedue to accelerometer bias and gyroscope drift and a long period of time, resulting in significantdeviation vessel. SLAM algorithms process that is under the process of creating a map landmarkof our environment and our estimate of the map and the position of the vessel. The purpose ofdata fusion is inertial navigation system and an external system to perform measurements withrelative position vessel. In order to increase navigation accuracy, reliability and an understandingof the environment, both navigation systems as well as the extended kalman filter as a tool foroptimal estimating the data fusion used by the navigation system. So for precise movement's anddevice is intended to be a detailed map of your surroundings. To track the exact position of thevessel must be marked. We use the SLAM algorithm that simultaneously considers these twocategories. Simulation results in MATLAB software environment for proper operation of theproposed algorithm illustrates a vessel navigation. Measurement error of inertial sensors cancompensate and prevent floating deviations from the desired path.

کلیدواژه ها

Autonomous Surface Vessel, Simultaneous Localization and Mapping (SLAM), ExtendedKalman Filter (EKF), Inertial Navigation System (INS), Sensor

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