Abstract:
Autonomous navigation is a crucial technology in the field of unmanned aerial vehicle (UAV), intelligent robots and smartcars. To overcome shortages in traditional visual navigation methods, a landmark fixed high-precision binocular visual autonomous navigation method, based on the camera egomotion estimation theory, was put forward. In this method, camera's egomotion parameters, velocity and angular velocity, were measured from the variance between frames of the continuing image sequence, then the position and attitude was calculated by accumulating the velocity and angular velocity. Moreover, by bringing in the absolute positioning information provided by the landmarks, the performance of the method in long time navigation was improved. Combining the absolute positioning information from the landmarks and the relative navigation information from the binocular vision, as well as modeling and decoupling the measurement noise of the binocular vision, the accumulation and increasing of the navigation error was suppressed. Simulation result shows that this method has the advantage of high precision, autonomy and completeness of navigation information.