Method and device for checking a calibration of environment sensors

Patent metadata

Field	Value
Publication number	US-11520038-B2
Application number	US-202016989973-A
Country	US
Kind code	B2
Filing date	Aug 11, 2020
Priority date	Aug 15, 2019
Publication date	Dec 6, 2022
Grant date	Dec 6, 2022

Abstract

A method for checking a calibration of N environmental sensors, wherein the N environmental sensors acquire an environment and each provide sensor data, N subfusions are formed from the acquired sensor data, each of the N subfusions leaves sensor data of one singular one of the N environmental sensors unconsidered upon the fusing, fusion results of the N subfusions are compared to one another, an incorrect calibration of the N environmental sensors is established based on a comparison result, and a check result is provided. Also disclosed are an associated device and a transportation vehicle.

First claim

The invention claimed is:

1. A device for a transportation vehicle, the device comprising:
at least three environmental sensors configured to detect an environment of the transportation vehicle and generate sensor data relative thereto; and
a control unit communicatively coupled to the at least three environmental sensors and configured to:
receive sensor data from the at least three environmental sensors,
generate a plurality of data subfusions, wherein each data subfusion is based on sensor data of a plurality of the at least three environmental sensors excluding sensor data of a different one of the at least three environmental sensors,
compare the plurality of data subfusions with one another to determine that a calibration of at least one of the at least three environmental sensors is incorrect and identify the at least one of the at least three environmental sensors as a decalibrated environmental sensor, and
generate, based on comparing the plurality of data subfusions with one another, an item of information to correct the calibration of the decalibrated environmental sensor.

2. The device of claim 1 , wherein the item of information identifies at least one of the decalibrated environmental sensor and at least one of the plurality of data subfusion that is error-free.

3. The device of claim 1 , wherein the control unit is configured to one of generate object hypotheses based on the sensor data of the at least three environmental sensors and receive the object hypotheses from the at least three environmental sensors, and wherein the control unit is configured to both generate the plurality of data subfusions and compare the plurality of data subfusions with one another based on the object hypotheses.

4. The device of claim 3 , wherein the object hypotheses include bounding boxes.

5. The device of claim 3 , wherein the control unit is configured to determine at least one translation matrix and/or at least one rotation matrix based on the object hypotheses, and wherein to compare the plurality of data subfusions to determine the decalibrated environmental sensor includes comparing the at least one translation matrix and/or the at least one rotation matrix or at least one value derived therefrom to at least one threshold value.

6. The device of claim 5 , wherein the control unit is configured to derive parameters for a cross calibration based on the at least one translation matrix and/or the at least one rotation matrix.

7. A transportation vehicle comprising:
at least three environmental sensors for acquiring sensor data related to an environment of the transportation vehicle; and
a control unit communicatively coupled to the at least three environmental sensors and configured to
receive sensor data from the at least three environmental sensors,
generate a plurality of data subfusions, wherein each data subfusion is based on sensor data of a plurality of the at least three environmental sensors excluding sensor data of a different one of the at least three environmental sensors,
compare the plurality of data subfusions with one another to determine that a calibration of at least one of the at least three environmental sensors is incorrect and identify the at least one of the at least three environmental sensors as a decalibrated environmental sensor, and
generate, based on comparing the plurality of data subfusions with one another, an item of information to correct the calibration of the decalibrated environmental sensor.

8. The transportation vehicle of claim 7 , wherein the item of information identifies at least one of the decalibrated environmental sensor and at least one of the plurality of data subfusion that is error-free.

9. The transportation vehicle of claim 7 , wherein the control unit is configured to one of generate object hypotheses based on the sensor data of the at least three environmental sensors and receive the object hypotheses from the at least three environmental sensors, and wherein the control unit is configured to both generate the plurality of data subfusions and compare the plurality of data subfusions with one another based on the object hypotheses.

10. The transportation vehicle of claim 9 , wherein the object hypotheses include bounding boxes.

11. The transportation vehicle of claim 9 , wherein the control unit is configured to determine at least one translation matrix and/or at least one rotation matrix based on the object hypotheses, and wherein to compare the plurality of data subfusions to determine the decalibrated environmental sensor includes comparing the at least one translation matrix and/or the at least one rotation matrix or at least one value derived therefrom to at least one threshold value.

12. The transportation vehicle of claim 9 , wherein the control unit is configured to derive parameters for a cross calibration based on the at least one translation matrix and/or the at least one rotation matrix.

13. A method for a transportation vehicle, the method comprising:
receiving, by a control unit, sensor data from at least three environmental sensors, wherein the sensor data includes data related to an environment of the transportation vehicle;
generating a plurality of data subfusions, wherein each data subfusion is based on sensor data of a plurality of the at least three environmental sensors and excluding sensor data of a different one of the at least three environmental sensors;
comparing the plurality of data subfusions with one another to determine that a calibration of at least one of the at least three environmental sensors is incorrect and identifying the at least one of the at least three environmental sensors as a decalibrated environmental sensor; and
generating, based on comparing the plurality of data subfusions with one another, an item of information to correct the calibration of the decalibrated environmental sensor.

14. The method of claim 13 , wherein the item of information identified at least one of the decalibrated environmental sensor and at least one of the plurality of data subfusion that is error-free.

15. The method of claim 13 , further comprising one of generating object hypotheses based on the sensor data of the at least three environmental sensors and receiving the object hypotheses from the at least three environmental sensors, wherein both generating the plurality of data subfusions and comparing the plurality of data subfusions with one another is based on the object hypotheses.

16. The method of claim 15 , wherein the object hypotheses include bounding boxes.

17. The method of claim 15 , further comprising determining at least one translation matrix and/or at least one rotation matrix based on the object hypotheses, wherein comparing the plurality of data subfusions to determine the decalibrated environmental sensor includes comparing the at least one translation matrix and/or the at least one rotation matrix or at least one value derived therefrom to at least one threshold value.

18. The method of claim 17 , further comprising deriving parameters for a cross calibration based on the at least one translation matrix and/or the at least one rotation matrix.

Assignees

• Volkswagen Ag

Inventors

• Steinmeyer Simon
• Schwithal Alexander

Classifications

• G01S17/931

  of land vehicles · CPC title

• B60W2050/041

  Built in Test Equipment [BITE] · CPC title

• G01S13/865

  Combination of radar systems with lidar systems · CPC title

• B60W50/04 Primary

  Monitoring the functioning of the control system · CPC title

• G01S7/4026

  Antenna boresight · CPC title