Vehicle Sensor Calibration Using Real-World Target Scans
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Solution Overview
Problem
Conventional sensor verification processes for vehicles are highly manual and costly, requiring skilled technicians and controlled calibration environments, which are expensive to set up and maintain, especially for testing the scanning range of long-range sensors.
Innovation Solution
A system that uses sensor data from vehicles operating in real environments to identify and repeatedly scan targets, comparing sensor data to calibrate, align, and verify the performance of sensors, thereby reducing the need for manual intervention and costly calibration setups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual sensor verification processes are used with controlled calibration environments, then sensor calibration accuracy is improved, but operational costs and setup complexity increase significantly
Solution Approach 1:
The system enables sensors to automatically verify and calibrate themselves by scanning targets in real-world environments and comparing sensor data against stored reference data, eliminating the need for manual technician intervention and complex controlled calibration environments
Solution Approach 2:
The system creates digital copies of target objects and stores them as reference data. During operation, sensor scans are automatically compared against these digital copies to verify sensor performance and detect drift, replacing the need for physical controlled calibration environments
2Reliability
If controlled calibration environments are set up for sensor verification, then sensor performance verification is improved, but operational costs increase
Solution Approach 1:
The system allows sensors to perform both operational scanning and self-verification functions using the same hardware and software resources. Sensors continuously scan targets during normal vehicle operation and automatically compare results against stored reference data, eliminating the need for separate calibration facilities and reducing operational costs
Solution Approach 2:
The system enables automatic sensor verification during normal vehicle operation by comparing sensor scans against stored reference data, eliminating the need for expensive controlled calibration environments and manual technician intervention while maintaining sensor reliability
3Measurement precision
If manual sensor verification processes are used, then sensor calibration accuracy is improved, but time consumption increases
Solution Approach 1:
The system performs sensor verification continuously during normal vehicle operation rather than requiring periodic manual calibration sessions. Sensors automatically scan targets and compare results against reference data in real-time, maintaining continuous calibration without interrupting vehicle operations or requiring technician time
Solution Approach 2:
The system enables sensors to automatically verify and calibrate themselves by comparing sensor data against stored reference data during normal operation, eliminating the need for manual technician intervention and significantly reducing time consumption while maintaining calibration accuracy
Data Source
AI summary
An example method involves detecting a sensor-testing trigger. Detecting the sensor-testing trigger may comprise determining that a vehicle is within a threshold distance to a target in an environment of the vehicle. The method also involves obtaining sensor data collected by a sensor of the vehicle after the detection of the sensor-testing trigger. The sensor data is indicative of a scan of a region of the environment that includes the target. The method also involves comparing the sensor data with previously-collected sensor data indicating detection of the target by one or more sensors during one or more previous scans of the environment. The method also involves generating performance metrics related to the sensor of the vehicle based on the comparison.