Calibration for autonomous vehicle operation

A method, comprising:

• receiving a plurality of sensor measurements from a plurality of sensors disposed about a vehicle, wherein the plurality of sensors comprise a LIDAR sensor configured to capture LIDAR sensor data and an image sensor configured to capture image sensor data;
• identifying, based at least in part on the plurality of sensor measurements, an anomalous sensor measurement of the plurality of sensor measurements associated with the image sensor of the plurality of sensors, wherein identifying the anomalous sensor measurement comprises:
• determining a set of edges in the LIDAR sensor data;
• associating, as region data, at least a portion of the image sensor data with the LIDAR sensor data;
• and
• identifying a portion of the region data that is anomalous;
• determining, based at least in part on the anomalous sensor measurement, that the image sensor is miscalibrated;
• generating an expected sensor measurement, associated with the image sensor;
• and
• generating, based at least in part on the expected sensor measurement, a calibration parameter for calibrating the image sensor.

One or more non-transitory computer readable media having instructions stored thereon which, when executed by one or more processors of a system, cause the system to perform operations comprising:

• receiving first sensor data associated with a first measurement made by a first sensor disposed about the system, the first sensor comprising an image sensor;
• receiving second sensor data associated with a second sensor disposed about the system, the second sensor comprising a LIDAR sensor;
• determining, based at least in part on the first sensor data and the second sensor data, that the first sensor data is anomalous, wherein determining that the first sensor data is anomalous comprises:
• detecting a set of detected edges in the second data;
• determining, as region data, at least a portion of the first sensor data with the set of detected edges;
• and
• determining, based at least in part on the region data, that the first sensor data is anomalous;
• and
• determining an expected sensor measurement based at least in part on the first measurement and the second sensor data;
• determining a calibration parameter associated with the first sensor based at least in part on the expected sensor measurement;
• and
• calibrating the first sensor based at least in part on the calibration parameter.