Dual-Distance Image Sensing for Interference-Resistant Range Finding
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Solution Overview
Problem
Conventional distance sensing techniques, such as LIDAR, face challenges in complex environments like busy highways due to signal interference and high processing demands, making them unsuitable for real-time applications like autonomous driving.
Innovation Solution
Utilizing image sensors to capture multiple images from different distances, analyzing parameters like object dimensions or irradiance to determine distance, reducing processing time through formulas like h1/h2=f1*(R1+dR)/f2*R1, b1/b2=Φ1*(R1+dR){circumflex over ( )}2/(Φ2*R1{circumflex over ( )}2, and employing range finders or position sensors for calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional distance sensing techniques like LIDAR are used, then distance measurement capability is achieved, but signal interference occurs in complex environments and processing time increases
Solution Approach 1:
The patent replaces active distance sensing systems (LIDAR, ultrasonic sensors) that emit signals with passive image sensing systems that capture reflected light. This substitution eliminates the harmful signal interference problem in complex environments while maintaining distance measurement capability through image analysis of object dimensions and irradiance
Solution Approach 2:
The patent changes the measurement parameters from analyzing returned signal characteristics (time, intensity) to analyzing image parameters (object dimensions, irradiance, area). This parameter transformation allows distance sensing through passive image capture without emitting signals, resolving the interference issue
2Measurement precision
If conventional distance sensing techniques like LIDAR are used, then distance measurement capability is achieved, but processing time and computational demand increase
Solution Approach 1:
The patent extracts only the essential distance-related information from images (object area, dimensions, irradiance) rather than processing complete point cloud data or performing complex signal analysis. This extraction approach significantly reduces processing time while maintaining measurement accuracy
Solution Approach 2:
The patent uses standard image sensors (cameras) that are inexpensive and widely available instead of expensive LIDAR systems. The image data can be quickly captured and processed, providing a cost-effective and time-efficient solution for distance measurement
3Productivity
If image sensors are used for distance sensing, then processing time is reduced and interference resistance is improved, but measurement precision must be maintained
Solution Approach 1:
The patent uses multiple image sensors positioned at different distances from the object to capture images from multiple dimensions. By comparing object parameters (area, dimensions, irradiance) across these different viewing distances, the system achieves accurate distance measurement while maintaining fast processing speeds
Solution Approach 2:
The patent introduces image parameters (object area, dimensions, irradiance) as intermediary measurements that can be quickly extracted from images and then used to calculate distance. This intermediary approach enables fast processing while maintaining measurement precision through the relationship between image parameters and actual distance
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Provides accurate and interference-resistant distance sensing suitable for autonomous driving and robotic applications by leveraging image analysis to determine object distance efficiently and quickly.
Implementation Method 1
image sensors are configured for detecting object distance based on images captured by the image sensors
Implementation Method 2
parameters within the images are analyzed to determine a distance of the object relative to the image sensors
Data Source
AI summary
In various embodiments, image sensors are configured for detecting object distance based on images captured by the image sensors. In those embodiments, parameters within the images are analyzed to determine a distance of the object relative to the image sensors. In some implementations, techniques for distance detecting object distance in accordance with the present disclosure are deployed within a vehicle. In those implementations, the distance sensing in accordance with the present disclosure can be used to aid various driving scenario, such as different levels of autonomous self-driving by the vehicle. In some implementations, the distance sensing can be employed in robotic equipment such as unmanned underwater devices to aid distance sensing of certain underwater objects of interest. In some implementations, the distance sensing can be employed in monitoring or surveillance for detecting or measuring object distance relative to a reference point.