Integration of Indoor Position and Navigation using Monocular SLAM and IMU

  • 麥 耘菁

Student thesis: Master's Thesis


GPS (Global Positioning System) dependent positioning and navigation has been developed over recent years and has been widely used for outdoor positioning and navigation However high-rise buildings or indoor environments can block the satellite signal Therefore many indoor positioning methods have been developed to respond to this issue In addition to measuring the distance using sonar and laser this research uses monocular simultaneous localization and mapping (MonoSLAM) combined with an inertial measurement unit (IMU) to build an indoor positioning system As time continues to move a vehicle MonoSLAM measures the distance between the image features and the camera (depth) Making use of the Extend Kalman Filter (EKF) MonoSLAM provides real-time position velocity and camera attitude Because the feature points will not always appear and can't be trusted at all times a wrong estimation will cause the position to diverge The integrated system in this thesis uses the multi-rate Kalman Filter to complement each method Finally the experiment using Virtual Studio C# is shown to measure the MonoSLAM data and IMU data and Matlab is used to verify the results
Date of Award2015 Aug 5
Original languageEnglish
SupervisorShau-Shiun Jan (Supervisor)

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