Joint Lidar Camera Calibration via Salient Feature Re-projection
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Solution Overview
Problem
Current systems for autonomous vehicles that rely solely on lidar or camera systems struggle to fully understand the environment and navigate effectively, as they require cumbersome human calibration and do not account for sensor drift over time, making them costly and prone to errors.
Innovation Solution
A semi-automated calibration system that uses a processing circuit to receive data from both lidar and camera systems, determine salient features, and adjust calibration settings based on re-projection errors, allowing for online recalibration and improved accuracy through the use of object detection systems and multi-tier threshold systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration methods are used for joint lidar and camera systems, then calibration can be performed, but the process becomes cumbersome and costly with high training requirements
Solution Approach 1:
The system performs self-calibration by automatically detecting salient features in both lidar and camera images, extracting corresponding points, and computing calibration parameters without human intervention. The processing circuit autonomously completes the entire calibration workflow from feature detection to parameter optimization.
Solution Approach 2:
The patent replaces manual mechanical calibration procedures with automated computational methods. Instead of physical adjustment and human observation, the system uses image processing algorithms, feature extraction techniques, and computational geometry to achieve calibration automatically.
2Reliability
If traditional calibration systems are used, then initial calibration can be established, but they cannot account for sensor drift over time requiring re-calibration
Solution Approach 1:
The system continuously monitors calibration quality by detecting salient features and computing re-projection errors. When drift is detected or calibration degrades over time, the system automatically initiates recalibration using the same automated pipeline, ensuring continuous reliability without manual intervention.
Solution Approach 2:
The patent enables continuous calibration maintenance through automated monitoring and recalibration cycles. Instead of a one-time calibration, the system maintains calibration validity over time by periodically checking and updating calibration parameters as needed.
3Productivity
If automated calibration systems are implemented, then calibration efficiency improves, but system complexity increases
Solution Approach 1:
The processing circuit performs multiple functions within the calibration system: feature detection, point extraction, correspondence matching, calibration parameter computation, and validation. By consolidating these functions in a single processing unit, the system achieves automation without proportionally increasing overall system complexity.
4Measurement precision
If human operators perform calibration, then calibration can be conducted, but training costs are high and operators cannot readily identify recalibration needs
Solution Approach 1:
The system autonomously performs calibration and monitors its own performance by detecting calibration quality metrics. It independently identifies when recalibration is needed based on predefined thresholds or degradation patterns, eliminating the need for trained human operators to recognize calibration status.
Data Source
AI summary
A calibration system includes a processing circuit configured to receive data corresponding to a first image where the data includes information corresponding to a 2D BEV of a scene, and to receive data corresponding to a second image where the data includes information corresponding to a 2D image of the scene. The processing circuit may determine a salient feature in the first image or the second image, and project, based on a first calibration setting, the salient feature from the first image to the second image or vice versa. The processing circuit may select a region corresponding to the projected salient feature in the first image or the second image, determine an identity of the salient feature, and determine a second calibration setting based on the identity of the salient feature and the selected region corresponding to the salient feature in the 2D BEV and the 2D image.