UAV-Based Perception Sensor Calibration System
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Solution Overview
Problem
Manual calibration of perception sensors on machines is time-consuming and prone to human error, and existing automated solutions are costly and complex.
Innovation Solution
An automated calibration system using an unmanned aerial vehicle (UAV) with a target of predetermined geometry that moves along a path to cover the sensor's field of view, providing accurate position and orientation data for the perception sensor calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration of perception sensor is conducted, then calibration can be performed with simple equipment, but the process is time-consuming and prone to human error
Solution Approach 1:
The calibration system performs self-calibration by automatically capturing images of the calibration target at multiple positions, processing the images through algorithms, and computing calibration parameters without requiring manual intervention. The system uses the known geometry of the calibration target and the captured images to automatically determine the perception sensor's parameters, eliminating human error and reducing calibration time.
2Productivity
If automated calibration system is implemented, then calibration speed and accuracy are improved, but the system becomes costly and complex
Solution Approach 1:
The calibration system is designed to be universally applicable to different types of perception sensors (cameras, LIDAR, radar) and can calibrate multiple sensors simultaneously. The same calibration target and image processing algorithms can be used across various sensor types, reducing the need for specialized equipment for each sensor type and lowering overall system complexity and cost.
Solution Approach 2:
A calibration target with known geometry serves as an intermediary object between the perception sensor and the calibration process. This target can be captured by different sensor types and processed through unified algorithms, acting as a universal mediator that simplifies the calibration process across multiple sensor types while maintaining accuracy.
3Measurement precision
If calibration target position is measured manually, then equipment cost is reduced, but position accuracy and geometry measurements become inaccurate
Solution Approach 1:
The system replaces manual mechanical measurement of the calibration target's position with automated image-based measurement. The perception sensor captures images of the calibration target, and processing algorithms automatically determine the target's position and orientation in 3D space, eliminating the need for complex mechanical measurement equipment while improving accuracy.
Data Source
AI summary
A calibration system for a machine is provided. The calibration system includes an unmanned aerial vehicle provided in association with a perception sensor. The unmanned aerial vehicle includes a target attached thereto. The unmanned aerial vehicle is configured to move along a predetermined path sweeping across a field of view of the perception sensor. The unmanned aerial vehicle is configured to present the target to the perception sensor, such that the target covers the field of view of the perception sensor based on the movement of the unmanned aerial vehicle along the predetermined path. The unmanned aerial vehicle is configured to determine and communicate an orientation and a position of the target to the calibration system.