Avision/inertia integrated positioningmethod using position and orientationmatchingwhich can be adopted on intelligent vehicle\nsuch as automated guided vehicle (AGV) and mobile robot is proposed in this work. The method is introduced firstly. Landmarks\nare placed into the navigation field and camera and inertial measurement unit (IMU) are installed on the vehicle. Vision processor\ncalculates the azimuth and position information from the pictures which include artificial landmarks with the known direction\nand position. Inertial navigation system (INS) calculates the azimuth and position of vehicle in real time and the calculated pixel\nposition of landmark can be computed from the INS output position. Then the needed mathematical models are established\nand integrated navigation is implemented by Kalman filter with the observation of azimuth and the calculated pixel position of\nlandmark. Navigation errors and IMU errors are estimated and compensated in real time so that high precision navigation results\ncan be got. Finally, simulation and test are performed, respectively. Both simulation and test results prove that this vision/inertia\nintegrated positioningmethod using position and orientationmatching has feasibility and it can achieve centimeter-level autonomic\ncontinuous navigation.
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