Vehicle Sensor Calibration Using Repeatable Motion Patterns
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Solution Overview
Problem
Autonomous vehicles face challenges in accurately calibrating their detection systems, which affects the precision of object location determination and overall operation, leading to inefficiencies and increased resource usage.
Innovation Solution
A method and system for calibrating multiple detection systems in a vehicle by moving it in repeatable patterns and using computing devices to collect and combine data points, determine corrections for each system, and adjust settings such as gain adjustments and orientation, ensuring accurate object detection and vehicle operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration methods are used for detection systems, then the calibration process is simple, but the accuracy of object location determination deteriorates
Solution Approach 1:
The system performs preliminary calibration by moving the vehicle through a predetermined pattern (such as a figure-eight pattern) before actual autonomous operation. This advance calibration establishes baseline detection accuracy and allows corrections to be applied during normal operation, thereby improving measurement precision without adding complexity during deployment.
Solution Approach 2:
The calibration system uses feedback from multiple detection systems (cameras, LIDAR, radar) to continuously monitor and adjust the accuracy of object location determination. By comparing detections across multiple systems and applying corrections based on known patterns, the system improves measurement precision while managing complexity through iterative refinement.
2Measurement precision
If multiple detection systems are calibrated individually, then each system can be optimized, but the overall calibration time increases
Solution Approach 1:
The system merges the calibration process for multiple detection systems into a single unified procedure. By moving the vehicle through a predetermined pattern that all detection systems observe simultaneously, the calibration of cameras, LIDAR, radar, and other sensors is performed concurrently rather than sequentially, reducing total calibration time while maintaining detection accuracy through integrated processing.
Solution Approach 2:
The predetermined movement pattern serves as a universal calibration target for all detection systems. The same figure-eight pattern or calibration course provides calibration data for cameras, LIDAR, radar, and other sensors simultaneously, allowing multiple systems to be calibrated using a single multi-functional approach rather than requiring separate calibration procedures for each system.
3Measurement precision
If calibration is performed frequently to maintain accuracy, then detection precision is improved, but resource consumption increases
Solution Approach 1:
The system implements periodic calibration at predetermined intervals or under specific conditions (such as before each trip or after certain events) rather than continuous calibration. This periodic approach maintains detection accuracy by ensuring calibration is performed regularly while significantly reducing energy consumption compared to continuous calibration operations.
Solution Approach 2:
The calibration system uses the vehicle's own movement through predetermined patterns as the calibration stimulus, eliminating the need for external calibration equipment or infrastructure. The vehicle calibrates itself by detecting known patterns in its environment during normal operation or dedicated calibration periods, reducing resource requirements while maintaining detection precision.
Data Source
AI summary
Aspects of the disclosure provide for a method of calibrating a vehicle's plurality of detection systems. To calibrate a first detection system, orientation data is collected using the first detection device when the vehicle faces a first direction and a second direction opposite the first direction. To calibrate a second detection system, data is collected using the second detection device while the vehicle moves in a repeatable pattern near a first object. To calibrate a third detection system, light reflected off a second object is detected using the third detection system as the vehicle is moved towards the second object. To calibrate a fourth detection system, data collected using the second detection system and the fourth detection system is compared. To calibrate a fifth detection system, radar signals reflected off a third object is received using the fifth detection system while the vehicle moves relative to the third object.