A map generated from ground-based 3D LIDAR data is a critical component for autonomous vehicle navigation using a vision based sensor. When the size of a map is large and the number of grid cells is relatively big, managing the map associated with a dense data set from 3D LIDAR scanner is a demanding task. Wavelets serve as the basis for an efficient compression scheme which makes it possible to significantly reduce processing effort to generate and manage a grid map in real-time. This paper proposes a novel approach to generate an occupancy map from compressed measurement signals. A one-dimensional Haar wavelet transform has been applied to compress 3D LIDAR data, from which occupancy maps have been generated. Our experimental results show that this method performs well to provide an autonomous vehicle with rich 3D environment information.

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