Abstract: A computer-implemented method analyzes radar data. The method includes acquiring the radar data from one or more radar sensors. The method includes processing the radar data to derive output data including spatial points with associated features. The method includes receiving the output data as input data. The method includes analyzing the radar data based on the input data.

Abstract: The present disclosure provides systems and techniques directed at object detection in a vehicle. In aspects, techniques include capturing current radar image data. The current radar image data includes at least one current point cloud. The current point cloud includes at least one current object point being related to an object, and each current object point includes spatial information related to the object. The techniques further include retrieving previous radar image data. The previous radar image data includes at least one previous point cloud. The previous point cloud includes at least one previous object point being related to the object, and each previous object point includes spatial information related to the object. The techniques further include concatenating the information from the current radar image data and the information from the previous radar image data to derive enhanced radar image data using a recurrent neural network.

Abstract: A computer implemented method for object detection includes: determining a grid, the grid comprising a plurality of grid cells; determining, for a plurality of time steps, for each grid cell, a plurality of respective radar detection data, each radar detection data indicating a plurality of radar properties; determining, for each time step, a respective radar map indicating a pre-determined radar map property in each grid cell; converting the respective radar detection data of the plurality of grid cells for the plurality of time steps to a point representation of pre-determined first dimensions; converting the radar maps for the plurality of time steps to a map representation of pre-determined second dimensions, wherein the pre-determined first dimensions and the pre-determined second dimensions are at least partially identical; concatenating the point representation and the map representation to obtain concatenated data; and carrying out object detection based on the concatenated data.

Abstract: A computer implemented method for determining a location of an object comprises the following steps carried out by computer hardware components: determining a pre-stored map of a vicinity of the object; acquiring sensor data related to the vicinity of the object; determining an actual map based on the acquired sensor data; carrying out image registration based on the pre-stored map and the actual map; carrying out image registration based on the image retrieval; and determining a location of the object based on the image registration.

Abstract: A method is provided for classifying a tracked object in an environment of a vehicle. The vehicle includes a plurality of radar sensors and a processing device configured to establish a neural network. According to the method, local radar detections are captured from an object in the environment of the vehicle via the radar sensors. Based on the local radar detections, point features and tracker features are determined. The point features are encoded via point encoding layers of the neural network, whereas the tracker features are encoded via track encoding layers of the neural network. A temporal fusion of the encoded point features and the encoded tracker features is performed via temporal fusion layers of the neural network. The tracked object is classified based on the fused encoded point and tracker features via classifying layers of the neural network.

Abstract: A method is provided for detecting objects by using a radar sensor and by using a device configured to establish a neural network. A plurality of raw radar data points is captured. At least one object class is defined comprising a predefined object type and a geometrical shape for enclosing an object. Via a first stage of the neural network, a semantic segmentation is performed for the data points regarding the object class and background, and for each data point, a rough approximation is estimated for a spatial condition of the geometrical shape. Based on this rough approximation and via a second stage of the neural network, a subset of the data points is selected based on the semantic segmentation, and for each data point of the subset, a refined approximation for the spatial condition of the geometrical shape and a confidence score for the refined approximation are estimated.

Abstract: A computer implemented method for detection of objects in a vicinity of a vehicle comprises the following steps carried out by computer hardware components: acquiring radar data from a radar sensor; determining a plurality of features based on the radar data; providing the plurality of features to a single detection head; and determining a plurality of properties of an object based on an output of the single detection head.

Abstract: A computer implemented method for object detection includes: determining a grid, the grid comprising a plurality of grid cells; determining, for a plurality of time steps, for each grid cell, a plurality of respective radar detection data, each radar detection data indicating a plurality of radar properties; determining, for each time step, a respective radar map indicating a pre-determined radar map property in each grid cell; converting the respective radar detection data of the plurality of grid cells for the plurality of time steps to a point representation of pre-determined first dimensions; converting the radar maps for the plurality of time steps to a map representation of pre-determined second dimensions, wherein the pre-determined first dimensions and the pre-determined second dimensions are at least partially identical; concatenating the point representation and the map representation to obtain concatenated data; and carrying out object detection based on the concatenated data.

Abstract: A computer implemented method for processing radar reflections includes receiving radar reflections by at least one radar sensor; determining a target angle under which radar reflections related to a potential target are received by the at least one radar sensor; and determining an energy of radar reflections received by the at least one radar sensor under a pre-determined angular region around the target angle.

Abstract: A method for formation of a compacted arrangement of articles to be packaged within a packaging machine, whereby the group of articles come into contact with and is guided through the packaging machine via at least one profiled bar, at least in a partial section of its transport route, which comes into contact with an end face of the group of articles and in doing so at least some of the articles of the group are pushed together in the compacted arrangement. A device for implementation of the method for formation of a compacted group of a plurality of the same type of articles to be packaged. A symmetrically or asymmetrically profiled thrust bar for transforming a group of articles being conveyed in a horizontal direction into a compacted arrangement.

Abstract: A wrapping device (10) for an apparatus (1) for enveloping and packaging a group (3) of articles (2) while they are being moved on a conveyor device (6) with a web-shaped material (4). The wrapping device (10) includes a rod-shaped wrapping element (14), which is laterally fixed to two parallely disposed circulating traction elements (12) on both sides of the conveyor device, whereby said wrapping element (14) is moved by these traction elements (12). The wrapping element (14) is further fixable largely form-lockingly and without play in corresponding receiving elements (16, 48) of the respective traction elements (12), whereby at least one of the receiving elements (16, 48) includes a securing element (20) that can be moved against the return force of a spring locking device (18).

Abstract: The invention relates to a method for formation of a compacted arrangement of articles (14) to be packaged within a packaging machine, whereby the group (12) of articles (14) come into contact with and is guided through the packaging machine by means of at least one profiled bar (30), at least in a partial section (20) of its transport route (18), which comes into contact with an end face of the group (12) of articles (14) and in doing so at least some of the articles (14) of the group (12) are pushed together in the compacted arrangement. The invention also relates to a device for implementation of the method for formation of a compacted group of a plurality of the same type of articles to be packaged. The invention also relates to a symmetrically or asymmetrically profiled thrust bar for transforming a group of articles being conveyed in a horizontal direction into a compacted arrangement.

Abstract: A wrapping device (10) for an apparatus (1) for enveloping and packaging a group (3) of articles (2) while they are being moved on a conveyor device (6) with a web-shaped material (4). The wrapping device (10) includes a rod-shaped wrapping element (14), which is laterally fixed to two parallely disposed circulating traction elements (12) on both sides of the conveyor device, whereby said wrapping element (14) is moved by these traction elements (12). The wrapping element (14) is further fixable largely form-lockingly and without play in corresponding receiving elements (16, 48) of the respective traction elements (12), whereby at least one of the receiving elements (16, 48) includes a securing element (20) that can be moved against the return force of a spring locking device (18).