Autonomous Vehicle Sensor Calibration Using Vehicle Feature Alignment
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Solution Overview
Problem
Existing sensor calibration methods for autonomous vehicles require human intervention, which is impractical when the vehicle is operating autonomously, and existing methods lack efficiency and accuracy in calibrating multiple sensors with varying orientations and types.
Innovation Solution
A method and system that utilizes vehicle features, such as a trailer, to calibrate sensors without human intervention, using timestamped data from multiple sensors and optimization processes to align coordinate systems, allowing for accurate extrinsic calibration of both similar and different types of sensors while the vehicle is moving.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If existing sensor calibration methods are used, then calibration can be performed, but human intervention is required which is impractical when the vehicle is operating autonomously
Solution Approach 1:
The calibration system uses the autonomous vehicle's own sensor data and detected environment features to perform self-calibration without external human intervention. The system leverages the vehicle's autonomous navigation capabilities to autonomously capture calibration images and compute calibration parameters, making the system serve itself.
Solution Approach 2:
The system performs calibration actions in advance during autonomous operation by capturing multiple images at different positions and orientations. These preliminary image captures enable the calibration computation to be performed before critical navigation decisions are made, ensuring accurate sensor alignment.
2Measurement precision
If traditional calibration methods are used, then calibration can be performed, but efficiency and accuracy are insufficient for calibrating multiple sensors with varying orientations and types
Solution Approach 1:
The calibration system is designed to handle multiple types of sensors (cameras, LIDAR, radar) with different orientations and detection ranges using a unified calibration approach. The system captures environment features that are visible to multiple sensor types simultaneously and computes calibration parameters that align all sensors in a common coordinate system.
Solution Approach 2:
The system captures calibration images from multiple dimensions by moving the vehicle to different positions and orientations in space. By collecting images across multiple spatial dimensions and combining them with detection results from sensors with varying detection ranges, the system achieves comprehensive calibration accuracy.
Data Source
AI summary
Systems and methods of calibrating sensors for an autonomous vehicle. A method includes detecting a first vehicle feature of the autonomous vehicle from one or more first sensors, detecting a second vehicle feature of the autonomous vehicle from one or more second sensors, and calibrating the one or more second sensors with the one or more first sensors based on the first vehicle feature and the second vehicle feature. A system includes one or more first sensors, one or more second sensors, and one or more controllers. The one or more controllers detect a first vehicle feature from the one or more first sensors, detect a second vehicle feature from the one or more second sensors, and calibrate the one or more second sensors with the one or more first sensors based on the first vehicle feature and the second vehicle feature.