Distance Sensor with Adjustable Focus Imaging and Lens Shift Compensation
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Solution Overview
Problem
Conventional distance sensors used in unmanned vehicles are bulky, expensive, and have limited field of view, making them unsuitable for compact applications, and they often suffer from lens shift and image magnification issues that affect triangulation accuracy.
Innovation Solution
A compact distance sensor that projects multiple beams to form measurement and reference patterns, allowing for simultaneous image capture and lens movement detection, which adjusts distance calculations to compensate for lens movement and improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of moving object
If conventional distance sensors are used for obstacle detection, then distance measurement capability is provided, but the sensors are bulky and have limited field of view
Solution Approach 1:
The imaging sensor is divided into multiple regions of interest (ROIs), each assigned to detect specific projection points. This segmentation allows parallel processing of multiple projection points across a wide field of view without requiring a single large sensor, thus reducing overall sensor volume while maintaining measurement precision through distributed detection.
Solution Approach 2:
The system transitions from traditional single-point or narrow-field distance measurement to multi-point simultaneous measurement across an expanded field of view. By projecting multiple beams and detecting their reflections across different spatial dimensions, the system achieves both compact size and high measurement precision through dimensional expansion of the detection space.
2Area of stationary object
If multiple projection points are activated to expand field of view, then coverage area increases, but system complexity increases
Solution Approach 1:
Multiple projection points and their corresponding detection regions are merged into a unified processing framework. The system combines the projection of multiple beams with simultaneous detection across multiple ROIs, processing all projection points through an integrated algorithm that calculates distances for multiple points in parallel, thereby expanding field of view without proportionally increasing system complexity.
Solution Approach 2:
The imaging sensor and processing system are designed to handle multiple functions simultaneously: projecting multiple beams, detecting reflections from multiple projection points, capturing images across a wide field of view, and calculating distances for multiple objects. This multi-functionality allows the system to expand field of view while maintaining manageable complexity through unified operation.
3Adaptability or versatility
If lens is made movable for focusing and zooming, then imaging flexibility improves, but lens shift and image magnification issues affect triangulation accuracy
Solution Approach 1:
The system implements feedback mechanisms where the detection of projection point positions and image characteristics provides information about lens state. This feedback allows the system to compensate for lens shift and image magnification effects, maintaining triangulation accuracy despite lens movement. The feedback loop continuously adjusts calculations based on actual observed positions, ensuring precision is preserved while allowing imaging flexibility.
Solution Approach 2:
The system dynamically adjusts calculation parameters based on lens position and imaging conditions. By changing the parameters used in triangulation calculations according to the actual lens state and observed image characteristics, the system maintains measurement precision even when lens flexibility is utilized for focusing and zooming operations.
4Measurement precision
If multiple projection points are simultaneously activated, then distance measurement capability is enhanced, but processing complexity increases
Solution Approach 1:
The processing task is segmented by assigning specific regions of interest in the image to detect specific projection points. This segmentation divides the complex task of processing multiple projection points into manageable sub-tasks, where each ROI independently processes its assigned projection points. The segmented approach enhances distance measurement capability through multi-point detection while reducing processing complexity through distributed, parallel processing.
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
The solution enables accurate distance measurement with a wide field of view, reduces manufacturing costs, and enhances the ability to capture clear images of moving objects, addressing the limitations of conventional sensors.
Implementation Method 1
capturing an image of the field of view, wherein the object, the reference pattern, and the measurement pattern are visible in the image
Data Source
Figure 1A~1B
Figure 2
Figure 3A
AI summary
In one embodiment, a method for calculating a distance to an object includes simultaneously activating a first projection point and a second projection point of a distance sensor to collectively project a reference pattern into a field of view, activating a third projection point of the distance sensor to project a measurement pattern into the field of view, capturing an image of the field of view, wherein the object, the reference pattern, and the measurement pattern are visible in the image, calculating a distance from the distance sensor to the object based on an appearance of the measurement pattern in the image, detecting a movement of a lens of the distance sensor based on an appearance of the reference pattern in the image, and adjusting the distance as calculated based on the movement as detected.