Angular Measurement via Overlapping Image Coordinate Transformations

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Solution Overview

Problem

Conventional surveying methods, such as those using theodolites, require expensive scales or encoders and have mechanical tolerance issues, limiting the accuracy and cost-effectiveness of angular measurements.

Innovation Solution

The method employs imaging devices to acquire overlapping images, determining correspondences between features and computing angular measurements without the need for scales or encoders, using coordinate transformations to calculate azimuth and elevation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional theodolites with scales or encoders are used, then angular measurements can be obtained, but the cost is high and mechanical tolerance issues limit accuracy

Engineering Contradiction:
Improveangular measurement accuracyVSAvoidmechanical components (scales/encoders)
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent replaces mechanical measurement systems (scales and encoders in theodolites) with an optical imaging system. Digital images are captured from multiple angles, and coordinate transformations are applied to calculate angular measurements computationally, eliminating the need for mechanical angular measurement components and their associated tolerance issues.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent creates a digital copy of the scene through imaging devices that capture images of target points. These digital image copies are then processed through coordinate transformations to derive angular measurements, replacing the need for direct mechanical angular measurement while preserving measurement accuracy.

Inventive Principle:
Principle #26Copying

2Extent of automation

If expensive scales or encoders are used in theodolites, then angular measurements can be automated, but the cost increases significantly

Engineering Contradiction:
Improveautomated angular measurementVSAvoidcost of scales/encoders
Core Design Contradiction:
Extent of automationVSDevice complexity

Solution Approach 1:

The patent replaces expensive mechanical automation components (encoders) with a computational approach. Images are captured by imaging devices, and automated coordinate transformations are applied to calculate angular measurements, achieving automation without the high cost of mechanical encoder systems.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If mechanical theodolites are used, then angular measurements can be taken, but mechanical tolerances limit the achievable accuracy

Engineering Contradiction:
Improveangular measurement accuracyVSAvoidmechanical tolerance stability
Core Design Contradiction:
Measurement precisionVSReliability

Solution Approach 1:

The patent eliminates mechanical measurement components that are subject to tolerance accumulation and degradation. By using imaging devices and computational coordinate transformations, the system achieves high measurement precision without the reliability issues inherent in mechanical tolerance chains.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS8818044B2Methods and apparatus for performing angular measurements
Publication Date: 2014.08.26 TRIMBLE INC
  • US8818044B2 patent drawing
  • US8818044B2 patent drawing
  • US8818044B2 patent drawing

AI summary

A method of determining an azimuth and elevation of a point in an image is provided. The method comprises positioning an imaging device at a first position and acquiring a first image. The method also comprises rotating the imaging device and acquiring a second image at the first position. The first image includes the point, and a portion of the first image overlaps a portion of the second image. The method also includes determining correspondences between features in overlapping portions of the images, determining a first transformation between coordinates of the first image and coordinates of the second image based on the correspondences, and determining a second transformation between the coordinates of the second image and a local coordinate frame. The method also includes computing the azimuth and elevation of the point based on the first transformation and the second transformation.