Multi-Sensor Calibration Validation for Vibration-Drifted AV Sensors
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Solution Overview
Problem
Autonomous vehicles face challenges in maintaining accurate sensor calibration due to vibrations during navigation, which can affect the precision of light detection and ranging sensors and RADAR systems, leading to potential navigation errors.
Innovation Solution
A system and method for validating sensor calibration using a combination of light detection and ranging sensors and imaging sensors, with a processor executing instructions to detect distances and intensity values from reflective and non-reflective surfaces, generating predicted aggregate locations, and determining alignment errors to initiate calibration processes when thresholds are exceeded.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensor types are used simultaneously for autonomous navigation, then navigation accuracy is improved, but sensor calibration complexity increases
Solution Approach 1:
The system performs self-calibration by automatically detecting alignment errors between sensors and adjusting calibration parameters without requiring manual intervention or external calibration equipment, thereby reducing calibration complexity while maintaining multi-sensor navigation accuracy
Solution Approach 2:
The system continuously monitors alignment errors between sensor data and provides feedback to adjust calibration parameters, enabling automatic compensation for calibration drift and reducing the need for complex manual recalibration procedures
2Measurement precision
If sensor calibration is performed manually, then calibration precision can be ensured, but time consumption increases
Solution Approach 1:
The system automatically performs calibration validation and adjustment by comparing sensor data with expected geometric relationships, eliminating the need for manual calibration operations while maintaining precision through algorithmic error detection and correction
Solution Approach 2:
The system pre-establishes geometric relationships and calibration criteria during system setup, enabling rapid automatic validation and calibration adjustments during operation without requiring time-consuming manual procedures
3Stability of the object's composition
If sensor positions are fixed to maintain calibration, then calibration stability is improved, but adaptability to vibrations and movements decreases
Solution Approach 1:
The system continuously monitors alignment errors caused by vibrations or position changes and provides feedback to adjust calibration parameters in real-time, maintaining calibration stability despite physical disturbances without requiring fixed sensor mounting
Solution Approach 2:
The system dynamically adjusts calibration parameters based on real-time sensor data and detected alignment errors, allowing the calibration state to adapt to changing physical conditions such as vibrations and movements rather than relying on fixed positions
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables timely and efficient self-calibration of sensors in autonomous vehicles, ensuring accurate navigation by adjusting algorithms and initiating calibration processes when alignment errors exceed predefined thresholds, thereby maintaining sensor precision and safety.
Implementation Method 1
at least one light detection and ranging sensor configured to detect a distance to at least one location associated with the substantially reflective portion of the at least one object
Implementation Method 2
at least one imaging sensor configured to detect light intensity values associated with the substantially reflective portion of the at least one location of the at least one object
Data Source
AI summary
Among other things, we describe systems and method for validating sensor calibration. For validating calibration of a system of sensors having several types of sensors, an object may be configured to have a substantially reflective portion such that the sensors can isolate the substantially reflective portion, and their sensor data can be compared to determine, if the detected locations of the substantially reflective portion by each sensor are aligned. For calibrating a system of sensors, an object having known calibration features can be used and detected by each sensor, and the detected data can be compared to known calibration data associated with the object to determine if each sensor is correctly calibrated.