Region-wide Coverage For The Mobile Robot At The Same Time Positioning And Map Building (slam) Technology

In the paper, the simultaneous localization and map building is used for the navigation system of a region-coverage autonomous mobile robot. Simultaneous map building and localization, which is defined as long-term globally referenced position estimation without a priori information, is difficult because of the following paradox: to move precisely, a mobile robot must have an accurate environment map; however, to build an accurate map, the mobile robot's sensing locations must be known precisely. To overcome this issue, the robot is equipped with a laser measurement system for a means in which a subset of environment features can be precisely learned from the robot's initial location and in boundary setting-up process. The subset of environment features is tracked to provide precise positioning subsequently. An algorithm is developed to extract feature lines from original data as environment features. The accumulated error has been eliminated by using data association and extended Kalman filter based feature tracking technique. The experimental result proves that the solution to the simultaneous map building and localization problem for region-coverage autonomous mobile robot is indeed possible and the method has higher computational efficiency and better localization accuracy.