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    OBJECT RECOGNITION AND CLASSIFICATION USING MULTIPLE SENSOR MODALITIES
    1.
    发明申请
    OBJECT RECOGNITION AND CLASSIFICATION USING MULTIPLE SENSOR MODALITIES 审中-公开

    公开(公告)号：US20180068206A1

    公开(公告)日：2018-03-08

    申请号：US15260141

    申请日：2016-09-08

    Applicant: Mentor Graphics Corporation

    Inventor： Matthias Arnold Pollach ,  Ljubo Mercep

    IPC: G06K9/62 ,  G06K9/00 ,  G06K9/32

    Abstract: Object recognition and classification based on data from multiple sensor modalities is disclosed. A computing system can detect an event in a monitored portion of an environment coordinate field associated with a vehicle. The computing system can retrieve data associated with the detected event from a plurality of modalities. At least one of the modalities can include raw data from a sensor associated with the vehicle. The computing system can classify the detected event based at least in part on the retrieved data and one or more parameters of a classifier.

    VEHICLE LOCALIZATION WITH MAP-MATCHED SENSOR MEASUREMENTS
    3.
    发明申请
    VEHICLE LOCALIZATION WITH MAP-MATCHED SENSOR MEASUREMENTS 审中-公开

    公开(公告)号：US20180066954A1

    公开(公告)日：2018-03-08

    申请号：US15419922

    申请日：2017-01-30

    Applicant: Mentor Graphics Corporation

    Inventor： Rainer Oder ,  Andreas Erich Geiger ,  Ljubo Mercep ,  Matthias Pollach

    IPC: G01C21/36 ,  G01C21/34

    Abstract: This application discloses a computing system to implement vehicle localization in an assisted or automated driving system. The computing system can receive an environmental model populated with measurement data captured by sensors mounted in a vehicle. The computing system can detect a location of the vehicle relative to the map data based on a correlation between the measurement data and the map data. The computing system can detect landmarks in the map data and switch to sparsely-populated map data from higher-definition map data for subsequent location detections. When the computing system does not detect a vehicle location, the computing system can track movement of the vehicle based on subsequent measurement data in the environmental model. After reacquiring a vehicle location, the computing can realign the tracked movement of the vehicle and measured data to the map data or modify the map data to include the tracked data.

    EVENT CLASSIFICATION AND OBJECT TRACKING
    4.
    发明申请
    EVENT CLASSIFICATION AND OBJECT TRACKING 审中-公开

    公开(公告)号：US20180067491A1

    公开(公告)日：2018-03-08

    申请号：US15419931

    申请日：2017-01-30

    Applicant: Mentor Graphics Corporation

    Inventor： Rainer Oder ,  Andreas Erich Geiger ,  Ljubo Mercep ,  Matthias Pollach

    IPC: G05D1/00 ,  G05D1/02 ,  G06F17/50

    Abstract: This application discloses a computing system to implement object tracking in an assisted or automated driving system of a vehicle. The computing system can assign a pre-classification to a detection event in an environmental model, update the environmental model with new sensor measurements and corresponding detection events over time, and track the detection event in the updated environmental model. The computing system can track the detection event by predicting a future state of the detection event with a state change model selected based on the assigned pre-classification, comparing the predicted future state to an actual future state of the detection event in an update to the environmental model, and determining the detection event corresponds to an object proximate to the vehicle based on the comparison. A control system for the vehicle can control operation of the vehicle based, at least in part, on the tracked detection event.

    Vehicle localization with map-matched sensor measurements
    5.
    发明授权
    Vehicle localization with map-matched sensor measurements 有权

    公开(公告)号：US10585409B2

    公开(公告)日：2020-03-10

    申请号：US15419922

    申请日：2017-01-30

    Applicant: Mentor Graphics Corporation

    Inventor： Ljubo Mercep ,  Matthias Pollach

    IPC: G01C21/36 ,  G01C21/34 ,  G05B17/02 ,  G05D1/00 ,  G05D1/02 ,  G06F16/29 ,  G06F17/50 ,  G01C21/28 ,  G01S13/931 ,  G01S15/931 ,  G01S17/93 ,  G08G1/16

    Abstract: This application discloses a computing system to implement vehicle localization in an assisted or automated driving system. The computing system can receive an environmental model populated with measurement data captured by sensors mounted in a vehicle. The computing system can detect a location of the vehicle relative to the map data based on a correlation between the measurement data and the map data. The computing system can detect landmarks in the map data and switch to sparsely-populated map data from higher-definition map data for subsequent location detections. When the computing system does not detect a vehicle location, the computing system can track movement of the vehicle based on subsequent measurement data in the environmental model. After reacquiring a vehicle location, the computing can realign the tracked movement of the vehicle and measured data to the map data or modify the map data to include the tracked data.

    Low-level sensor fusion
    7.
    发明授权
    Low-level sensor fusion 有权

    公开(公告)号：US10317901B2

    公开(公告)日：2019-06-11

    申请号：US15287537

    申请日：2016-10-06

    Applicant: Mentor Graphics Corporation

    Inventor： Rainer Oder ,  Andreas Erich Geiger ,  Ljubo Mercep ,  Matthias Pollach

    IPC: G05D1/00 ,  G05D1/02 ,  G06K9/00

    Abstract: This application discloses a computing system to implement low-level sensor fusion in an assisted or automated driving system of a vehicle. The low-level sensor fusion can include receiving raw measurement data from sensors in the vehicle and temporally aligning the raw measurement data based on a time of capture. The low-level sensor fusion can include spatially aligning measurement coordinate fields of the sensors into an environmental coordinate field based, at least in part, on where the sensors are mounted in the vehicle, and then populating the environmental coordinate field with raw measurement data captured by the sensors based on the spatial alignment of the measurement coordinate fields to the environmental coordinate field. The low-level sensor fusion can detect at least one detection event or object based, at least in part, on the raw measurement data from multiple sensors as populated in the environmental coordinate field.

    SENSOR EVENT DETECTION AND FUSION
    8.
    发明申请
    SENSOR EVENT DETECTION AND FUSION 审中-公开

    公开(公告)号：US20180067463A1

    公开(公告)日：2018-03-08

    申请号：US15419914

    申请日：2017-01-30

    Applicant: Mentor Graphics Corporation

    Inventor： Rainer Oder ,  Andreas Erich Geiger ,  Ljubo Mercep ,  Matthias Pollach

    IPC: G05B17/02 ,  G05D1/00 ,  G05D1/02

    Abstract: This application discloses a computing system to implement sensor event detection and fusion system in an assisted or automated driving system of a vehicle. The computing system can monitor an environmental model to identify spatial locations in the environmental model populated with temporally-aligned measurement data. The computing system can analyze, on a per-sensor basis, the temporally-aligned measurement data at the spatial locations in the environmental model to detect one or more sensor measurement events. The computing system can utilize the sensor measurement events to identify at least one detection event indicative of an object proximate to the vehicle. The computing system can combine the detection event with at least one of another detection event, a sensor measurement event, or other measurement data to generate a fused detection event. A control system for the vehicle can control operation of the vehicle based, at least in part, on the detection event.

    Event classification and object tracking
    10.
    发明授权
    Event classification and object tracking 有权

    公开(公告)号：US10520904B2

    公开(公告)日：2019-12-31

    申请号：US15419931

    申请日：2017-01-30

    Applicant: Mentor Graphics Corporation

    Inventor： Ljubo Mercep ,  Matthias Pollach

    IPC: G05B17/02 ,  G05D1/00 ,  G05D1/02 ,  G06F16/29 ,  G01C21/34 ,  G01C21/36 ,  G06F17/50 ,  G01C21/28 ,  G01S13/93 ,  G01S15/93 ,  G01S17/93 ,  G08G1/16 ,  G01S13/86 ,  G01S7/48 ,  G06K9/00 ,  G06F16/583 ,  G01S13/72

    Abstract: This application discloses a computing system to implement object tracking in an assisted or automated driving system of a vehicle. The computing system can assign a pre-classification to a detection event in an environmental model, update the environmental model with new sensor measurements and corresponding detection events over time, and track the detection event in the updated environmental model. The computing system can track the detection event by predicting a future state of the detection event with a state change model selected based on the assigned pre-classification, comparing the predicted future state to an actual future state of the detection event in an update to the environmental model, and determining the detection event corresponds to an object proximate to the vehicle based on the comparison. A control system for the vehicle can control operation of the vehicle based, at least in part, on the tracked detection event.

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