Multi-focal feature tracking for a human-assisted mobile robot

In the project Autonomous City Explorer, an interactive robot is designed to find its way to a given destination in unknown urban environments by interacting with pedestrians. Considering applications in a human dominated environment, the robot can be sent to a destination by tracking a landmark selected by users and described by 2D image features. To achieve a natural landmark selection from the user perspective and an accurate feature tracking for a safe robot navigation, the robot preselects visual features and presents the users only the image regions providing higher tracking accuracy. Furthermore, a multi-focal camera system is used to extend the sensing range. SIFT, Harris corner and optical flow used for tracking and self-localization are compared and applied to different visual sensors. A coordination strategy is realized, in which the camera with wide field of view is used for robot orientation control and the high-resolution camera is applied for robot forward motion control. The performance is experimentally evaluated.

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