Multi-Camera Ego-Motion Calibration for Vehicle Navigation
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating due to the vast amount of data they need to process and store, which can limit their navigation capabilities, especially when relying on traditional mapping technology.
Innovation Solution
A multi-camera navigation system that uses ego-motion information to calibrate camera positions and orientations, enabling efficient data processing and navigation by analyzing images from multiple cameras onboard the vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional mapping technology is used for autonomous vehicle navigation, then navigation capabilities can be provided, but the vast amount of data needed to process and store limits navigation capabilities
Solution Approach 1:
The patent extracts and removes the dependency on traditional GPS mapping technology by implementing a vision-based navigation system that uses monocular camera footage and visual odometry algorithms to determine vehicle position and orientation, thereby eliminating the need to process and store vast amounts of mapping data
Solution Approach 2:
The patent replaces the mechanical/GPS-based navigation system with a vision-based system that uses computer vision algorithms to process camera images and extract navigation information, substituting optical processing for traditional mechanical/GPS-based approaches
2Measurement precision
If multiple cameras are used to improve navigation accuracy, then obstacle detection and lane tracking improve, but device complexity increases
Solution Approach 1:
The patent makes the single monocular camera perform multiple functions by using it for both obstacle detection and lane tracking through visual odometry, eliminating the need for multiple specialized cameras and reducing system complexity
Solution Approach 2:
The patent enables the vision processing system to perform multiple navigation tasks including position estimation, orientation determination, obstacle detection, and lane tracking using the same camera and processing algorithms, thereby avoiding the complexity of multiple dedicated camera systems
Data Source
AI summary
The present disclosure relates to systems and methods for calibrating a multi-camera navigation system for a vehicle. In one implementation, at least one processing device may receive first and second image frames acquired by a first camera onboard the vehicle; receive first and second image frames acquired by a second camera onboard the vehicle; determine a first ego-motion signal, including an indication of a change in position of the first camera relative to capture times associated with the first and second image frames acquired by the first camera; determine a second ego-motion signal, including an indication of a change in position of the second camera relative to capture times associated with the first and second image frames acquired by the second camera; and determine a relative orientation between the first camera and the second camera based on the first ego-motion signal and the second ego-motion signal.