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This work consists of obtaining and processing data from three-dimensional
a stereo sensor with the main objective to develop a mechanism of perception to support systems
driving. The process begins with the camera calibration data for the sensor
with the best possible quality, to facilitate further processing,
whose initial step is based on point cloud filtering to remove
noise and reducing the amount of data.
The next step consists of determining the set of points that represent
the ground in the point cloud, so that it is possible to estimate the navigable area of the vehicle
and consequently the number of obstacles which is in this area.
The purpose is to carry out the segmentation of the various obstacles relative to the plane
the ground and waterways within the area in two ways: the first approach involves the application of the algorithm
Targeting the Euclidean point cloud sensor stereo, and the second is the
implementation of a region growing algorithm for application to the two-dimensional data
segmented lasers. The developed methods are tested under real conditions and are analyzed
failure situations, advantages and drawbacks of a relatively other.


