Lidar Sensor Validation Using Fiducial Target Point Cloud Fitting
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Solution Overview
Problem
Lidar sensors used in autonomous vehicles have varying degrees of accuracy, consistency, and build quality, which can lead to inconsistencies in data, posing a risk to safe and predictable vehicle operation. It is crucial to validate lidar sensors to ensure they meet performance standards, especially in critical applications like autonomous vehicles where accuracy and reliability are paramount.
Innovation Solution
A method for validating lidar sensors through the generation of objective validation measurements by acquiring point clouds from the sensors, selecting points corresponding to a fiducial target, and fitting them to a geometric representation to calculate validation measurements, ensuring only validated sensors are used, thereby increasing accuracy and consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If lidar sensors are used in autonomous vehicles without validation, then device complexity is reduced and ease of manufacture is improved, but measurement precision and reliability deteriorate due to varying accuracy and consistency
Solution Approach 1:
The patent implements preliminary validation of lidar sensors before deployment in autonomous vehicles. A validation system performs measurements on lidar sensors using fiducial targets with known geometries, generating validation measurements that confirm whether sensors meet minimum performance standards. This preliminary action ensures measurement precision is established before the sensors are used in critical applications.
Solution Approach 2:
The validation system enables lidar sensor manufacturers and deployers to self-validate sensors using standardized procedures and fiducial targets. The system provides tools and methods that allow entities to independently assess sensor performance without requiring external certification, thereby maintaining measurement precision while reducing overall system complexity.
2Reliability
If lidar sensors from multiple manufacturers with varying build quality are used, then adaptability and versatility are improved, but reliability deteriorates due to inconsistencies in sensor performance
Solution Approach 1:
The patent establishes minimum performance parameters and thresholds that lidar sensors must meet regardless of manufacturer. The validation system measures specific parameters such as measurement accuracy, consistency, and precision against defined standards. Sensors from any manufacturer can be used if they meet these parameter requirements, ensuring reliability while maintaining adaptability across different manufacturers and sensor types.
Solution Approach 2:
The validation system creates a universal standard applicable to lidar sensors from any manufacturer. The same fiducial targets, measurement procedures, and evaluation criteria are used regardless of sensor origin, enabling consistent reliability assessment across diverse sensor types while preserving the ability to select from multiple manufacturers based on performance rather than brand.
3Measurement precision
If validation measurements are performed on all lidar sensors, then measurement precision is improved, but loss of time increases due to the validation process duration
Solution Approach 1:
The validation system performs measurements on multiple fiducial targets and collects multiple measurements per target, but only the measurements necessary to determine compliance with minimum standards are required. The system can stop validation once sufficient evidence of compliance or non-compliance is obtained, avoiding unnecessary measurement time while maintaining measurement precision through adequate sampling.
Solution Approach 2:
The validation system performs quick preliminary assessments using fiducial targets with known geometries that enable rapid measurement and evaluation. By using pre-configured targets with specific geometric features optimized for quick detection and measurement, the system achieves accurate validation results in minimal time, reducing the loss of time associated with comprehensive validation.
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
This approach ensures that only validated lidar sensors with consistent performance are used, enhancing the reliability and accuracy of sensor data, critical for safe navigation and passenger safety in autonomous vehicles.
Implementation Method 1
Light detection and ranging (lidar) sensors are used in a wide variety of applications and involve illuminating the target with laser light and measuring the reflected light with a sensor
Implementation Method 2
The laser return times and wavelengths are then used, for example, to determine the distance of a target
Data Source
AI summary
Various aspects of the subject technology relate to a lidar validation system. The lidar validation system is configured to acquire one or more lidar point clouds from a lidar unit, wherein the lidar unit comprises one or more lasers, and wherein each point cloud is a representation of a scene according to a laser in the lidar unit, the scene comprising a fiducial target. The lidar validation system is configured to generate, based on points in the one or more point clouds, a target cloud that correspond to the fiducial target, perform a rigid body processing to minimize a sum of distances from each point in the target cloud to the fiducial target, and generate lidar validation measurements based on the distances from each point in the target cloud to the fiducial target.