公开(公告)号：US20220221303A1

公开(公告)日：2022-07-14

申请号：US17647306

申请日：2022-01-06

Applicant: Aptiv Technologies Limited

Inventor： Mirko Meuter ,  Christian Nunn ,  Weimeng Zhu ,  Florian Kaestner ,  Adrian Becker ,  Markus Schoeler

IPC: G01C21/00 ,  G01S13/89 ,  G01S19/41 ,  G06T7/30 ,  G06T7/73 ,  G06N3/08

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.

公开(公告)号：US20220188582A1

公开(公告)日：2022-06-16

申请号：US17643586

申请日：2021-12-09

Applicant: Aptiv Technologies Limited

Inventor： Weimeng Zhu ,  Florian Kaestner ,  Zhiheng Niu ,  Arne Grumpe

IPC: G06K9/62 ,  G06N3/04 ,  G01S13/88

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.

公开(公告)号：US20220026568A1

公开(公告)日：2022-01-27

申请号：US17384493

申请日：2021-07-23

Applicant: Aptiv Technologies Limited

Inventor： Mirko Meuter ,  Jittu Kurian ,  Yu Su ,  Jan Siegemund ,  Zhiheng Niu ,  Stephanie Lessmann ,  Saeid Khalili Dehkordi ,  Florian Kästner ,  Igor Kossaczky ,  Sven Labusch ,  Arne Grumpe ,  Markus Schoeler ,  Moritz Luszek ,  Weimeng Zhu ,  Adrian Becker ,  Alessandro Cennamo ,  Kevin Kollek ,  Marco Braun ,  Dominic Spata ,  Simon Roesler

IPC: G01S13/931 ,  G06K9/00 ,  G06K9/62 ,  G01S13/86 ,  G01S7/41 ,  B60W60/00 ,  G06N3/04

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.

公开(公告)号：US20190325241A1

公开(公告)日：2019-10-24

申请号：US16374138

申请日：2019-04-03

Applicant: Aptiv Technologies Limited

Inventor： Christian Nunn ,  Weimeng Zhu ,  Yu Su

IPC: G06K9/00

Abstract: A device for extracting dynamic information comprises a convolutional neural network, wherein the device is configured to receive a sequence of data blocks acquired over time, each of said data blocks comprising a multi-dimensional representation of a scene. The convolutional neural network is configured to receive the sequence as input and to output dynamic information on the scene in response, wherein the convolutional neural network comprises a plurality of modules, and wherein each of said modules is configured to carry out a specific processing task for extracting the dynamic information.