On-Board Sensor Recalibration Using Route Landmarks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing sensor calibration methods for autonomous vehicles are inefficient, as they require dedicated calibration panels and impose a significant computational burden, limiting the frequency and accuracy of recalibrations, especially when sensors become misaligned over time.
Innovation Solution
A system and method that determine whether sensors are calibrated, decide on the need for recalibration based on error amounts and frequencies, and select appropriate landmarks for recalibration along the vehicle's route, minimizing computational load and ensuring accurate recalibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional calibration panels are installed to calibrate on-board sensors, then calibration accuracy is improved, but device complexity and operational restrictions increase
Solution Approach 1:
The patent replaces physical calibration panels with virtual calibration targets embedded in the environment (such as QR codes, AR markers, or naturally occurring features). These virtual targets are captured by the sensor itself and processed through image recognition algorithms, eliminating the need for dedicated calibration hardware while maintaining calibration accuracy.
Solution Approach 2:
The sensor system performs self-calibration by using its own captured images to identify calibration targets and compute calibration parameters. The system automatically detects features in the environment, matches them against known target patterns, and adjusts its internal parameters without requiring external calibration equipment or manual intervention.
2Reliability
If continuous sensor data collection is performed regardless of vehicle behavior, then data completeness is improved, but computational burden increases
Solution Approach 1:
The patent implements dynamic sensor data collection where the sampling rate and collection scope are adjusted based on vehicle state. During normal cruising, sensors operate at lower rates, but automatically increase resolution and frequency during critical events such as lane changes, intersections, or detected obstacles, ensuring data completeness only when necessary.
Solution Approach 2:
Instead of continuous collection, the system uses periodic sampling intervals adapted to driving conditions. The sensor controller monitors vehicle behavior and environmental factors, then activates full-spectrum data collection only during periods when calibration or critical monitoring is needed, reducing overall computational load while maintaining reliability.
3Measurement precision
If all sensor data is transmitted to central computing system, then data processing accuracy is improved, but system response time and bandwidth requirements worsen
Solution Approach 1:
The patent divides the computing architecture into distributed edge nodes (local processors near sensors) and a central cloud system. Critical time-sensitive processing such as obstacle detection and calibration verification is performed locally at the edge, while only essential calibration data and non-time-critical analysis are transmitted to the central system, reducing bandwidth requirements and improving response time.
Solution Approach 2:
The system performs preliminary processing and filtering of sensor data at the source before transmission. Calibration targets are identified and validated locally, with only confirmed calibration data and essential measurements transmitted to the central system, reducing data volume and transmission time while maintaining processing accuracy.
Data Source
AI summary
A system comprises a sensor system comprising a sensor and an analysis engine configured to determine whether the sensor is uncalibrated. The system further comprises an error handling system configured to determine whether to perform a recalibration in response to the sensor system determining that the sensor is uncalibrated. The error handling system further comprises a recalibration engine configured to perform a recalibration.