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Design and Optimization of Positioning System for Hull Crawling Robot

Nasiri, Hamid Reza | 2021

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 53945 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Khorasanchi, Mahdi; Tabeshpour, Mohammad Reza
  7. Abstract:
  8. The hulls of various ships are exposed to the problem of biofoulings on the hull after a period of time due to use in the salt water environment of the sea and the existence of suitable conditions for the growth of marine plants, so that the ship after about one month of stopping in the port, in order to start the activity again, it is necessary to clean the hull from these biofoulings. The ship will be transported to the dry dock for cleaning only when it is heavily involved in biofoulings on the hull, and in the meantime, it must be periodically cleaned in water by other systems, including the diver and robotic systems.Using a robotic system to perform this operation has various challenges. One of these challenges is the discussion of designing a positioning system for an underwater robot with two objectives of better control of the robot in underwater conditions and the other is the need to provide a report of different areas of the ship involved in biofoulings to the client in the first phase and before cleaning.This research has been done with the aim of designing and optimizing the positioning system of the ship's hull inspection robot. Underwater positioning methods are generally inertial, geophysical and acoustic positioning systems due to the special conditions and lack of access to the Global Positioning System (GPS). Due to the special conditions of using the robot that is connected to the hull of the ship and performs inspection by moving on the hull, the efficiency of these systems, access to equipment and other factors involved, the inertial positioning system as the system used to perform the positioning operation selected. In order to increase the accuracy of the system and due to the efficiency of the robot, the combined method of distance measurement using an encoder was used. The IMU provides a quick response in the short term, but position estimation errors are amplified due to the nature of integration and other factors. The encoder fails due to systematic and non-systematic errors, so in order to improve the results and compensate for the weaknesses of each system, the IMU and encoder sensor data were combined using a Kalman filter
  9. Keywords:
  10. Odometry ; Kalman Filters ; Distance Measurement ; Inspection Robot ; Inertial Navigation System ; Hull Crawling Robot ; Hull Inspection

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