Abstract: A method of generating input data for a machine learning model includes determining, for a sensor, a point cloud with points detected by the sensor from surfaces in the environment of the sensor, generating a preliminary target sensor point cloud for a target sensor by transforming, for the sensor, points of the determined point cloud into points from the perspective of the target sensor according to the relative position of the target sensor to the sensor, generating a target sensor point cloud for the target sensor by using the preliminary target sensor point cloud, wherein points which, due to one or more surfaces for which points exist in the preliminary target sensor point cloud, are not detectable by the target sensor are eliminated in the target sensor point cloud, and using the target sensor point cloud as input for the machine learning model.

Abstract: A computer-implemented method for classification of at least one object in an environment of a vehicle. The method includes: collecting first data from a first sensor within a first data collecting frame; collecting second data from at least a second sensor within a second data collecting frame; determining a first object representation using the first data; determining a second object representation using the second data; updating the first and/or second object representation depending on an arrival of third data from the at least second sensor collected in a third data collecting frame after the first data collecting frame; fusing the first and second representation to determine an updated representation of the object based on the received data; applying the updated representation for training the data-driven model as input data for a data-driven model to obtain output data containing an information about a classification of the detected object.

Abstract: A method of generating input data for a machine learning model includes determining, for a sensor, a point cloud with points detected by the sensor from surfaces in the environment of the sensor, generating a preliminary target sensor point cloud for a target sensor by transforming, for the sensor, points of the determined point cloud into points from the perspective of the target sensor according to the relative position of the target sensor to the sensor, generating a target sensor point cloud for the target sensor by using the preliminary target sensor point cloud, wherein points which, due to one or more surfaces for which points exist in the preliminary target sensor point cloud, are not detectable by the target sensor are eliminated in the target sensor point cloud, and using the target sensor point cloud as input for the machine learning model.

Abstract: A method and device for calibrating a sensor system of a moving object. The sensor system includes a plurality of individual sensors. Each individual sensor has a particular detecting range. Each of these sensors having a detecting range at least partially overlapping with at least one further sensor of the sensor system. The method includes: defining a virtual overall sensor based on a merger of the particular detecting ranges of each individual sensor; determining first coordinates of a plurality of external objects, as well as second coordinates of selected points of the moving object; and orienting the virtual overall sensor relative to the moving object, as a function of the first and second coordinates.

Abstract: A method and device for calibrating a sensor system of a moving object. The sensor system includes a plurality of individual sensors. Each individual sensor has a particular detecting range. Each of these sensors having a detecting range at least partially overlapping with at least one further sensor of the sensor system. The method includes: defining a virtual overall sensor based on a merger of the particular detecting ranges of each individual sensor; determining first coordinates of a plurality of external objects, as well as second coordinates of selected points of the moving object; and orienting the virtual overall sensor relative to the moving object, as a function of the first and second coordinates.