Abstract: A method for detecting objects in a radar system. The method includes: providing radar measurement values as a list of points, wherein each point comprises associated features; creating object hypotheses based on the radar measurement values by means of a trained artificial neural network, comprising the steps of: creating a feature map based on the radar measurement values, creating a probability distribution over the feature map, wherein each probability maximum corresponds to the most probable keypoint of an object, regression for each keypoint, filtering the probability maxima, and outputting an object hypothesis for each keypoint. A radar system for performing such a method is also described.

Abstract: A system for detecting objects based on data from at least one environmental sensor. An encoder is configured to process encoder input data that specify data from the at least one environmental sensor, wherein a representation is generated from the encoder input data, which representation represents information about located objects that is contained in the encoder input data. An object detection model is configured to process the generated representation as model input data and to generate object hypotheses from the representation generated by the encoder. The object hypotheses in each case include an object position and/or object features, wherein the object features comprise at least one of a bounding box and a classification.

Abstract: A system, a device, and a method for detecting objects by separately processing point clouds including information about the surroundings of the system and/or the device. The method includes: separating a point cloud into a plurality of point clouds according to one or more features of a plurality of features of each point of the point cloud; preprocessing the plurality of point clouds in a plurality of input paths of a network corresponding to the respective point cloud; fusing the output data of the plurality of input paths of the network; and further processing the fused output data in the network to detect the objects.

Abstract: A device for evaluating sensor data of a sensor device. The device includes an interface that receives the sensor data from the sensor device. A computing device provides input data to an artificial neural network based on the received sensor data and the artificial neural network uses the input data to output output data for evaluating the sensor data. The computing device adjusts parameters of the artificial neural network using a memory state, wherein the memory state depends on latent features of the artificial neural network relating to a previous calculation step.

Abstract: A method for processing sensor data, wherein the sensor data are present as a point cloud of individual points. The points are projected into at least two rasters with different resolutions. Points from a subregion of the point cloud are projected into a first raster with higher resolution and further points of the point cloud are projected into a second raster with lower resolution. Attributes from the first raster are compressed and arranged in the second raster before the attributes from the second raster are compressed.

Abstract: A method for generating training data for an object detector. The method includes receiving a plurality of optical images of a scene, each camera showing the scene from a respective viewing direction of a plurality of different viewing directions, receiving a plurality of sensor data elements, each sensor data element including sensor data other than optical image data of the scene from a respective sensing direction of a plurality of different sensing directions, training a first neural radiance field using the plurality of optical images to generate, for each 3D point of the scene, a respective value of a predetermined feature, training a second neural radiance field using the plurality of sensor data elements to generate, for each 3D point of the scene, a respective sensor data value and generating training data elements for the object detector using the first and the second neural radiance field.

Abstract: A method for planning a trajectory for an at least partially automated vehicle. The method includes: providing a trained machine learning model for determining the occupancy of an occupancy grid, the machine learning model is trained to predict the occupancy of the occupancy grid at a subsequent time from a history of occupancies; generating a temporal sequence of occupancies of the occupancy grid using measurement data from the environment of the vehicle; evaluating, using the trained machine learning model, the sequence of occupancies that were generated, to predict a total occupancy of the occupancy grid at a current time; comparing the predicted occupancy of the occupancy grid at a current time to the occupancy determined using measurement data, determining a location-dependent measure of a reliability of the occupancy information depending on the comparison; planning a trajectory for the at least partially automated vehicle based on the reliability.

Abstract: A distributed ontology system including a central computer comprising a global ontology directory, a plurality of ontology server computers, each including a repository of class and relation definitions, and a server for responding to queries relating to class and relation definitions in the repository, and a computer network connecting the central computer with the plurality of ontology server computers. A method is also described and claimed.

Abstract: A data query system including a first storage medium including a data schema having a data schema query language associated therewith, a second storage medium including an ontology model including classes and properties, the ontology model having an ontology query language associated therewith, wherein constructs of the database schema are mapped to corresponding classes, properties or compositions of properties of the ontology model, and an ontology query processor generating a query expressed in the data schema query language corresponding to a specified query expressed in the ontology query language. A method is also described and claimed.

Abstract: An instance browser including a repository of class and relation definitions, a server for responding to queries relating to class and relation definitions in the repository, and a graphical user interface including icons for representing instances of classes. A method is also described and claimed.

Abstract: A data query system including a first storage medium including a data schema having a data schema query language associated therewith, a second storage medium including an ontology model including classes and properties, the ontology model having an ontology query language associated therewith, wherein constructs of the database schema are mapped to corresponding classes, properties or compositions of properties of the ontology model, and an ontology query processor generating a query expressed in the data schema query language corresponding to a specified query expressed in the ontology query language. A method is also described and claimed.

Abstract: A data query system including a first storage medium including a data schema having a data schema query language associated therewith, a second storage medium including an ontology model including classes and properties, the ontology model having an ontology query language associated therewith, wherein constructs of the database schema are mapped to corresponding classes, properties or compositions of properties of the ontology model, and an ontology query processor generating a query expressed in the data schema query language corresponding to a specified query expressed in the ontology query language. A method is also described and claimed.

Abstract: An enterprise application system including a run-time transformation server, and a message broker for routing and transforming data in the form of messages between a source application and a target application, including a plug-in for preparing requests to the run-time transformation server and for processing responses from the run-time transformation server. A method is also described and claimed.