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Mapping an outdoor environmnent for path planning

We present an incremental map building approach that is applied by a group of cooperating heterogeneous robots. Robots cooperate by sharing information in order to build their own maps. Environment information comes into the mapping process from two different sources: aerial images from a helicopter and sonar readings from several ground robots. Ground robots use the resulting map to plan paths towards goal positions. These paths avoid detected obstacles and are updated when there is new information about an obstacle obstructing them. Finally, we consider environment uncertainty depending on the reliability of the information. We use uncertainty as an estimation of the real existence of detected obstacles and we apply it in order to plan paths that may need to go trough non-real obstacles.