Vehicle Sensor Calibration Course With 3D Targets and Obstacles
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Solution Overview
Problem
Existing sensor calibration methods for vehicles, particularly autonomous and semi-autonomous vehicles, are inefficient and lack repeatability, leading to potential inaccuracies and safety concerns.
Innovation Solution
The implementation of calibration courses with drivable paths, calibration targets, and obstacles that allow for precise sensor calibration and validation, utilizing three-dimensional targets with angled side surfaces to enhance detection capabilities and minimize shadowing, along with planar surfaces for LiDAR systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional sensor calibration methods are used, then calibration can be performed, but the calibration process is inefficient and lacks repeatability
Solution Approach 1:
The calibration course is segmented into multiple distinct calibration targets positioned at different locations and orientations along a drivable path. Each target provides specific calibration data for different sensor fields of view, allowing systematic calibration of the entire sensor suite through sequential detection as the vehicle traverses the course.
Solution Approach 2:
The calibration targets are pre-positioned in known locations with predetermined orientations and configurations before the calibration process begins. This preliminary setup creates a known reference environment that enables repeatable calibration measurements when the vehicle passes through the course.
2Measurement precision
If three-dimensional calibration targets with angled side surfaces are used, then detection capabilities are enhanced and shadowing is minimized, but the complexity of the calibration course increases
Solution Approach 1:
Different portions of the calibration targets have different geometric properties - angled side surfaces in regions where shadowing would occur and planar surfaces in regions optimized for LiDAR detection. This local differentiation of surface qualities optimizes detection accuracy for different sensor types and viewing angles without requiring all targets to be uniformly complex.
Solution Approach 2:
The calibration targets utilize three-dimensional geometry with surfaces extending in multiple dimensions and orientations. This adds spatial dimensionality to the calibration process, allowing targets to be detected from various angles and distances, thereby enhancing measurement precision while distributing the complexity across multiple spatial dimensions rather than concentrating it in a single plane.
3Measurement precision
If calibration courses with multiple targets and obstacles are implemented, then sensor calibration accuracy improves, but the time and resources required for calibration increase
Solution Approach 1:
The calibration course is designed as a universal test environment that can calibrate multiple sensor types (cameras, LiDAR, radar) simultaneously using the same set of targets and path. Each target serves multiple calibration functions for different sensors, allowing comprehensive calibration in a single traversal rather than requiring separate calibration procedures for each sensor type.
Solution Approach 2:
The calibration process maintains continuous useful action as the vehicle traverses the course, with sensors continuously detecting calibration targets throughout the drive path. The obstacles and turns are integrated into the driving route rather than requiring separate positioning maneuvers, ensuring that the vehicle is in motion the entire time and continuously gathering calibration data without idle repositioning.
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
The solution provides repeatable and reliable sensor calibration, reducing maintenance downtime and improving vehicle safety and efficiency by ensuring accurate sensor functionality.
Implementation Method 1
The calibration target can be used with a LiDAR system and is configured to receive a beam from the LiDAR system and reflect the beam back to the LiDAR system
Data Source
AI summary
Provided are systems and methods related to calibration courses and calibration targets, which can be configured for calibrating sensors used in vehicles, such as vehicles that include autonomous or semi-autonomous vehicle systems, or other mobile robots. As an example, a system can include a drivable path comprising a plurality of turns, a plurality of calibration targets proximate to the drivable path, and a plurality of obstacles in the drivable path. The plurality of calibration targets are positioned so as to be detectable by at least one sensor of a vehicle as the vehicle traverses the drivable path, and at least one particular obstacle of the plurality of obstacles changes an angle of the at least one sensor relative to at least one calibration target as the vehicle traverses the drivable path.