[[abstract]]In this project we design an autonomous wheeled robot for day and night patrol of an outdoor campus environment, mainly focusing on integration of cameras and various kinds of sensors to recognize salient landmarks, build the environment map and navigate around the environment autonomously. For this purpose, we will reconstruct a mobile robot equipped with ultrasonic sensors, GPS, digital compass, inertial sensors, laser range finder, IBDMS and IR/CCD camera system to gather environmental information. Then various visual techniques will be developed to recognize landmarks. For example, the color or texture feature can be used to classified cement, grass, or red brick areas, which helps determine the pavement and road edge. Fusion of multiple ultrasonic sensors and cameras may facilitate the detection of walls of a building. With IR images, the lamps can be easily detected by threshold at gray level of image pixels. Based on the rough positioning by GPS and digital compass, the position errors can be further reduced by detecting and tracing salient features, like SIFT features or Harris-Laplace features, with least square error fitting or Kalman filter method, and calculate the real distance between any two objects to achieve a three- dimensional localization by IBDMS method. Then, by deriving inverse sensor model of various sensors, the probabilistic grid map method can be applied to build the environment map. Finally, Then by utilizing the feedback linearization technique, a visual servo controller will be developed to successfully navigate the patrol robot moving along the road edge or artificial IR reflective lane markings.
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