Lidar Angular Offset Calibration Using Vehicle Moveable Components
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Solution Overview
Problem
Autonomous vehicles and robots face inaccuracies in determining object locations due to misalignment of reference axes between different sensors, leading to faulty decision-making and incorrect object positioning.
Innovation Solution
A method and system that utilize a dual-use component, such as a rotating wheel or robotic arm, to calibrate LIDAR sensors by capturing distance and offset data, identifying an offset error, and correcting future offset angles to align with a predefined vehicle reference axis, thereby ensuring accurate sensor data integration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple sensors are used to generate output data for autonomous vehicle decision-making, then the capability to identify obstacles and plot courses is improved, but the accuracy of object location determination deteriorates due to misalignment of reference axes between sensors
Solution Approach 1:
A calibration target with known geometric features serves as an intermediary object to establish the relationship between different sensor reference axes. The target includes distinctive patterns (such as concentric circles or geometric shapes) that enable computation of transformation parameters, allowing alignment of sensor coordinate systems without requiring physical adjustment of sensors themselves.
Solution Approach 2:
The patent replaces mechanical alignment procedures with computational methods. Instead of physically adjusting sensor mounting to achieve perfect alignment, the system uses image processing and geometric computation to calculate and store transformation parameters that mathematically correct for axis misalignment, substituting mechanical precision with computational correction.
2Measurement precision
If a dedicated calibration component is added to the vehicle, then LIDAR calibration accuracy is improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The calibration target is designed to serve multiple functions: it acts as a reference object for LIDAR calibration, provides geometric information for camera calibration, and can be used for sensor alignment verification. This multi-functionality eliminates the need for separate calibration components for different sensing systems, reducing overall device complexity while maintaining calibration accuracy.
Solution Approach 2:
The system performs self-calibration using the calibration target without requiring external intervention. The autonomous vehicle captures images of the target with its sensors, automatically computes transformation parameters, and stores calibration data in memory, enabling the vehicle to calibrate itself without manual setup or specialized equipment.
3Measurement precision
If manual calibration procedures are used, then calibration precision can be maintained, but time consumption and operational complexity increase
Solution Approach 1:
The calibration target is pre-configured with known geometric patterns and dimensions before being mounted in the vehicle. This preliminary preparation of the target with encoded geometric information enables the system to perform rapid automated calibration without requiring complex measurement procedures or manual adjustment during the calibration process itself.
Solution Approach 2:
Manual calibration procedures are replaced with automated image processing and computational algorithms. The system automatically captures images of the calibration target, extracts geometric features through computer vision, computes transformation parameters, and stores calibration data without human intervention, significantly reducing calibration time while maintaining precision through computational accuracy.
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 allows for accurate calibration of LIDAR sensors without additional hardware, reducing manufacturing complexity and enabling precise decision-making by aligning sensor data with a common reference axis, improving navigation and object detection accuracy.
Implementation Method 1
capturing, as the moveable component rotates, distance and offset data of the moveable component using a LIDAR sensor attached to the vehicle
Data Source
AI summary
Embodiments herein describe using a moveable component on a vehicle to calibrate a sensor (e.g., a LIDAR sensor). While a LIDAR sensor can be calibrated using a specially designed configuration component mounted on a vehicle, this increases the cost of manufacturing the vehicle and complexity for identifying a suitable location for the calibration component. Rather than adding a new component, embodiments herein use a moveable component already part of the design of the vehicle as a calibration component. That is, the embodiments herein use components that are primarily used for a different purpose to also perform LIDAR calibration, such as a wheel or a robotic arm.