Abstract
The central task for mobile robot operations is to compute the accurate position of the robot in the environment. The paper presents robust and efficient approach to refinement of a robot position focused on compensation of cumulative positioning errors. The system introduces a lidar range finder to improve the basic dead-reckoning system based on standard wheel encoders. As the lidar measurements are reliable the refinement procedure is based on comparison of two succeeding range measurements or comparison of the new measurement with the world map. The obtained data are pre-processed and the fusion algorithm is performed. The fusion provides primitives - line approximations of obstacle contours. The next step incorporates solving of occlusions on determined line segments and conducts search for line pairs in two consequent frames. Therefore in the end a segment-to-segment correspondence is used to determine a relative position change within two consequent frames. These methods of construction of the point pairs ensures good robustness of the approach. Achieved results have been experimentally tested in indoor office environments.
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