Whenever a mobile robot is required to navigate beyond its sensory horizon, it must either rely on potentially ineffective or misleading local search strategies (such as the ‘bug algorithms’ [Lum87]) or use some kind of world model to store cues for navigation. Such a world model is generally called a ‘map’ and can either be provided a priori or built online using a mapping algorithm. The mapping approaches can be separated into world-centric or robot-centric. World-centric systems represent the pose of all objects including the robot of the environment according to a fixed coordinate frame. In indoor scenarios, a corner of a room or a fixed position in the entrance area of an apartment is often used. To specify positions in the operational environment of the robot in outdoor applications, global coordinate systems like the latitude, longitude, and height system, the Earth Centered, Earth Fixed Cartesian coordinate system, the World Geographic Reference System or WGS 84 (GPS) are often used. World-centric mapping is mainly employed for tasks like navigation or path planning while robot-centric approaches are used for piloting tasks such as collision avoidance. Using matrix-based coordinate transformations, it is possible to convert between these different reference frames.
KeywordsMobile Robot Decomposition Tree Touch Sensor Occupancy Grid Virtual Edge
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