Robert Boschgmbh

Daimler Ag

Mercedes-benz Group Ag

Martin Meinke

Philipp Lehner

Helmuth Eggers

David Peter

Markus Gressmann

Sebastian Buck

Manuel Schaefer

Blooming in a lidar measurement is recognized using a distance from a lidar reflection point determined in an active measurement and a passive measurement. A first distance value is determined in the active measurement, based on a signal duration of a laser pulse, and a second distance value is determined in the passive measurement, based on a triangulation of two-dimensional intensity measurements carried out from different measuring positions. Blooming is identified when the second distance value exceeds the first distance value by a pre-determined amount.

Method and device for the recognition of blooming in a lidar measurement

A method and apparatus for detecting surroundings around a vehicle may include the step of periodically scanning the surroundings in a first detection region by a laser scanner. The method may also include detecting the surroundings in a second detection region by an optical camera. The first detection region and the second detection region may at least overlap each other. An optical sensor in the camera may be exposed at least twice within one period of the laser scanner. A first exposure time for a first exposure of the at least two exposures of the optical sensor may be chosen and synchronized with the laser scanner so that the first exposure occurs within a first time window, in which the laser scanner scans the first detection region.

Method and apparatus for detecting surroundings, and vehicle with such an apparatus

A method for generating a digital image pair for training a neural network to correct noisy image components of noisy images includes determining an extent of object movements within an overlapping region of a stored first digital image and a stored second digital image of an environment of a mobile platform, and determining a respective acquired solid angle of the environment of the mobile platform of the first and second digital images. The method further includes generating the digital image pair from the first digital image and the second digital images, when the respective acquired solid angles of the environment of the first and the second digital image do not differ from one another by more than a defined difference, and the extent of the object movements within the overlapping region of the first and the second digital image is less than a defined value.

Method for generating digital image pairs as training data for neural networks

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Hildrizhausen, Germany

Martin Meinke