Visual Front-End Processing for Camera Overlap Distortion Correction
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Solution Overview
Problem
Autonomous vehicles require high-definition maps and optical networks for safe operation, but existing systems lack efficient methods to process optical sensor data streams quickly and accurately, leading to potential safety issues due to optical distortion and parameter drift in cameras.
Innovation Solution
A compute system with a visual simultaneous localization and mapping (SLAM) mechanism that corrects optical distortion by analyzing overlap regions in sensor data from multiple cameras, calculates correction distances, and determines GPS coordinates to enhance data processing efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional optical sensor data processing methods are used, then system complexity is low, but processing speed and accuracy deteriorate due to optical distortion and parameter drift
Solution Approach 1:
The patent segments the optical sensor data processing into multiple stages: raw data acquisition, overlap region identification, feature line detection, distortion calculation, and correction application. This segmentation allows each module to specialize in specific tasks, improving processing speed while keeping individual module complexity manageable.
Solution Approach 2:
The system performs preliminary actions by pre-identifying overlap regions between multiple optical sensors and pre-calculating distortion parameters before actual data processing. This preliminary preparation enables faster real-time processing and reduces computational burden during critical operation phases.
2Measurement precision
If optical distortion correction is not applied, then system complexity is low, but measurement precision deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors optical sensor data for distortion patterns, calculates correction parameters based on identified feature lines, and applies corrections iteratively. This feedback loop ensures high measurement precision by constantly adjusting for optical distortions and parameter drift.
Solution Approach 2:
The system replaces complex mechanical calibration procedures with computational methods. Instead of physically adjusting optical sensors to eliminate distortion, the patent uses algorithmic approaches to detect and correct distortion in software, significantly reducing measurement precision while simplifying the overall system.
3Reliability
If multiple optical sensors are used to cover all sides of the environment, then reliability improves, but data processing overhead increases
Solution Approach 1:
The patent extracts and processes only the critical overlap regions where multiple optical sensors capture the same field of view. By isolating and focusing computational resources on these specific regions rather than processing all sensor data uniformly, the system maintains high operational reliability through multi-sensor coverage while significantly reducing processing overhead.
Data Source
AI summary
A compute system includes: a control circuit configured to: store a sensor data stream of a region of interest provided by optical sensors, analyze an overlap region of the sensor data stream to identify a feature line that is viewed by a first optical sensor and a second optical sensor of the optical sensors, calculate a correction distance, measured in pixels, for the first optical sensor by a position correction of the feature line in the overlap region, correct an optical distortion of the first optical sensor in the sensor data stream for the region of interest by applying the correction distance, and calculate GPS coordinates of the feature line for controlling a device.