IMU data offset compensation for an autonomous vehicle

1. An autonomous vehicle control system for an autonomous vehicle, comprising:

one or more processors; and

a memory storing an instruction set that, when executed by the one or more processors, causes the autonomous vehicle control system to:

receive sensor data from a sensor system of the autonomous vehicle, the sensor data comprising a sensor view of a surrounding environment of the autonomous vehicle;

receive inertial measurement unit (IMU) data from one or more IMUs of the autonomous vehicle;

based on comparing the IMU data with the sensor data from the sensor system, determine an IMU data offset from a reference; and

dynamically compensate for the IMU data offset.

2. The autonomous vehicle control system of claim 1 , wherein the executed instruction set causes the autonomous vehicle control system to generate an offset compensation transform in response to determining that the IMU data offset is within a set of plausibility thresholds.

3. The autonomous vehicle control system of claim 2 , wherein the executed instructions cause the autonomous vehicle control system to dynamically compensate for the IMU data offset by dynamically executing the offset compensation transform on the IMU data.

4. The autonomous vehicle control system of claim 1 , wherein the one or more IMUs comprise three or more IMUs, and wherein the executed instruction set causes the autonomous vehicle control system to further identify the IMU data offset from based on comparing IMU data from at least two other IMUs of the three or more IMUs with the IMU data offset.

5. The autonomous vehicle control system of claim 1 , wherein the executed instruction set further causes the autonomous vehicle control system to:

dynamically perform sequential localization operations by dynamically comparing the sensor view with a current localization map of a set of stored localization maps on the autonomous vehicle, the current localization map comprising ground truth data of a particular road segment on which the autonomous vehicle currently operates.

6. The autonomous vehicle control system of claim 5 , wherein the sequential localization operations are dynamically performed at a first rate, and wherein the IMU data from the one or more IMUs are received at a second rate that is greater than the first rate.

7. The autonomous vehicle control system of claim 6 , wherein the executed instruction set further causes the autonomous vehicle control system to:

based on the IMU data, determine a current state of the autonomous vehicle at the second rate;

for each localization operation, determine a map-relative state of the autonomous vehicle; and

between each sequential localization operation, correlate the map-relative state from a previous localization operation with the current state to determine whether the map-relative state from the previous localization operation is within a set of tolerance thresholds from the current state of the autonomous vehicle as determined from the IMU data.

8. The autonomous vehicle control system of claim 7 , wherein each of the map-relative state and the current state correspond to at least one of an orientation, a trajectory, a position in a local reference frame, a position in a global reference frame, or a velocity of the autonomous vehicle.

9. The autonomous vehicle control system of claim 7 , wherein the sequential localization operations correspond to a map-relative filter, and wherein determining the current state of the autonomous vehicle based on the IMU data corresponds to a continuous pose filter.

10. The autonomous vehicle control system of claim 1 , wherein the IMU data offset is produced by a deficient IMU comprising at least one of a faulty IMU, a damaged IMU, or a poorly calibrated IMU.

11. A method of operating an autonomous vehicle control system of an autonomous vehicle, the method being performed by one or more processors and comprising:

receiving sensor data from a sensor system of the autonomous vehicle, the sensor data comprising a sensor view of a surrounding environment of the autonomous vehicle;

receiving inertial measurement unit (IMU) data from one or more IMUs of the autonomous vehicle;

based on comparing the IMU data with the sensor data from the sensor system, determining an IMU data offset from a reference; and

dynamically compensating for the IMU data offset.

12. The method of claim 11 , wherein the one or more processors generate an offset compensation transform in response to determining that the IMU data offset is within a set of plausibility thresholds.

13. The method of claim 12 , wherein the one or more processors dynamically compensate for the IMU data offset by dynamically executing the offset compensation transform on the IMU data.

14. The method of claim 11 , wherein the one or more IMUs comprise three or more IMUs, and wherein the one or more processors further identify the IMU data offset based on comparing the IMU data from at least two other IMUs of the three or more IMUs with the IMU data offset.

15. The method of claim 11 , further comprising:

dynamically performing sequential localization operations by dynamically comparing the sensor view with a current localization map of a set of stored localization maps on the autonomous vehicle, the current localization map comprising ground truth data of a particular road segment on which the autonomous vehicle currently operates.

16. The method of claim 15 , wherein the sequential localization operations are dynamically performed at a first rate, and wherein the IMU data from the one or more IMUs are received at a second rate that is greater than the first rate.

17. The method of claim 16 , further comprising:

based on the IMU data, determining a current state of the autonomous vehicle at the second rate;

for each localization operation, determining a map-relative state of the autonomous vehicle; and

between each sequential localization operation, correlating the map-relative state from a previous localization operation with the current state to determine whether the map-relative state from the previous localization operation is within a set of tolerance thresholds from the current state of the autonomous vehicle as determined from the IMU data.

18. The method of claim 17 , wherein each of the map-relative state and the current state correspond to at least one of an orientation, a trajectory, a position in a local reference frame, a position in a global reference frame, or a velocity of the autonomous vehicle.

19. The method of claim 17 , wherein the sequential localization operations correspond to a map-relative filter, and wherein determining the current state of the autonomous vehicle based on the IMU data corresponds to a continuous pose filter.

20. A non-transitory computer readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to:

receive sensor data from a sensor system of an autonomous vehicle, the sensor data comprising a sensor view of a surrounding environment of the autonomous vehicle;

receive inertial measurement unit (IMU) data from one or more IMUs of the autonomous vehicle;

based on comparing the IMU data with the sensor data from the sensor system, determine an IMU data offset from a reference; and

dynamically compensate for the IMU data offset.