Mobile robot map updating using attributed fuzzy tournament matching

The maintenance of a map of a mobile robot's surroundings is essential to its autonomous operation. The decision on when to add, delete or modify the abstacle descriptions should be made frequently. These decisions are based on the comparison of sensory data (vision, ultrasonic or laser interferometry) with a-priori information in the map. In this paper, the attributed fuzzy tournaments are suggested as a nonlinear data structure to represent the uncertainty in the contents of the map and the sensory data. An algorithm to compute the level of match between the map and the perceived image of the surrounding obstacles is introduced.