Abstract
Building a Cartesian Elevation Map (CEM) is the required step that allows a path planning subsystem to find a possible way for an autonomous vehicle to go. The (CEM) should provide a 3-D world model for the mobile robot and should be simple enough to permit a fast obstacle detection. The aim of this work is to present a fast CEM reconstruction algorithm that also recovers the position and the size of the obstacles for both indoor and outdoor scenes. Obstacles detection is directly performed on the range image (sensor map). The algorithm is able to classify each pixel in the CEM as unexplored, occluded (the algorithm gives the maximum possible elevation), traversable and obstacle. The method is tested on both an outdoor scene of rocks and an indoor scene of blocks and green plants.
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