Vehicle Sensor Self-Calibration Using Stationary Structures
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Solution Overview
Problem
Existing methods for calibrating vehicle sensors require additional sensor systems or rely on standardized markers, making them inefficient and dependent on specific conditions.
Innovation Solution
A method that detects surrounding data using a vehicle's sensor, selects suitable stationary structures for calibration, and stores their positions, allowing for self-calibration without additional sensors by comparing instantaneous positions with stored ones after parking, thereby calibrating the sensor based on deviations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If additional sensor systems or standardized markers are used for calibration, then calibration accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The sensor system performs self-calibration by using its own sensor data to detect stationary structures and calculate calibration parameters, eliminating the need for additional calibration sensors or standardized markers. The system serves its own calibration needs using existing sensors and environmental features.
Solution Approach 2:
Stationary structures in the environment serve as intermediary objects that mediate the calibration process. Instead of requiring specialized calibration equipment, the system uses naturally occurring stationary structures (buildings, trees, signs) as reference objects to determine sensor calibration parameters.
2Reliability
If additional sensor systems are used for calibration, then calibration reliability is improved, but ease of operation deteriorates
Solution Approach 1:
The system automatically performs calibration without requiring external calibration equipment or complex setup procedures. The sensor system uses its own data and environmental features to self-calibrate, making the process simple and reliable.
Solution Approach 2:
The calibration method works with various types of sensors (cameras, LIDAR, radar) and various types of stationary structures, making it universally applicable across different sensor systems and environments without requiring specialized calibration equipment for each sensor type.
3Measurement precision
If standardized markers are required for calibration, then measurement precision is improved, but adaptability deteriorates
Solution Approach 1:
The system uses stationary structures in the environment as intermediary reference objects instead of standardized markers. This allows calibration to be performed using naturally occurring features like buildings, trees, and signs that are already present in the operational environment.
Solution Approach 2:
The calibration method is adaptable to different environments by using various types of stationary structures as reference objects. The system can calibrate in urban, suburban, and rural environments using whatever stationary structures are available, without requiring specific standardized markers.
Data Source
AI summary
A method/system for calibrating a vehicle sensor, including detecting data about the vehicle's surroundings using the sensor, and ascertaining stationary structures using the detected first data pieces. Stationary structures are selected for later calibration, and potential parking positions are determined. A parking position is selected from the potential parking positions so that after parking, stationary structures selected for a calibration of the sensor are in the sensor's field of vision. The vehicle is parked, and the position of the stationary structures selected for the calibration of the sensor is stored. After the vehicle start, second data pieces about the vehicle's surroundings are detected using the sensor, and instantaneous positions of the selected stationary structures are ascertained using the detected second data pieces. The instantaneous position are compared with the stored positions, and deviations between the instantaneous positions and the stored positions determined. The sensor is calibrated using the determined deviations.