FIELD: physics.
SUBSTANCE: method comprises determining, based on a training point cloud formed by a lidar sensor and representing the surrounding space of an unmanned vehicle, a plurality of lidar features, for each training object in the surrounding space, a plurality of complementary features based on statistical data on the coverage of the training objects with lidar points, obtaining a mark characterizing the degree of deterioration of the training point cloud data, generating a feature vector from a plurality of feature vectors based on a plurality of lidar features, a plurality of complementary features and a mark, training a machine learning algorithm based on a plurality of feature vectors to determine the degree of deterioration at the stage of using measurement data of the use stage generated by the lidar sensor.
EFFECT: disclosed is a system and a method for determining the degree of deterioration of point cloud data from a lidar sensor of an unmanned vehicle using a machine learning algorithm.
20 cl, 9 dwg
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