Dimensioning System Error Model Correction
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Solution Overview
Problem
Dimensioning systems face errors in measuring irregularly shaped objects and combining multiple objects, leading to inaccurate measurements, which are exacerbated by temperature variations and limited flexibility in measurement setups.
Innovation Solution
A method that projects a light pattern onto an object, captures and analyzes distortions to compute 3D data, selects a dimension to estimate, retrieves an error model from a library based on predictor variables, and subtracts the error estimate from the intermediate dimension estimate to obtain a final accurate measurement, using a minimum-volume-bounding box and distinct error models for length, width, and height.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If non-contact dimensioning systems are used to automate measurements, then measurement speed and productivity are improved, but measurement accuracy deteriorates due to systematic errors
Solution Approach 1:
The system uses measured objects to generate feedback in the form of error models that are stored in a library. These error models capture systematic errors and are subsequently applied to correct measurements of new objects, creating a continuous improvement loop that enhances accuracy while maintaining automated measurement speed
Solution Approach 2:
Error models are pre-computed and stored in a library before actual measurements are taken. When measuring a new object, the system retrieves relevant error models from the library and applies corrections in advance, eliminating the need for time-consuming manual calibration for each measurement while maintaining high accuracy
2Measurement precision
If strict requirements are placed on measurement setup to reduce errors, then measurement accuracy is improved, but system flexibility and ease of operation deteriorate
Solution Approach 1:
The system automatically adapts to different measurement conditions by changing parameters such as selecting appropriate error models from the library based on object characteristics, measurement geometry, and environmental conditions. This allows accurate measurements without requiring strict setup requirements or manual intervention
3Measurement precision
If manual physical measurement is used to ensure accuracy, then measurement precision is improved, but productivity and measurement speed deteriorate
Solution Approach 1:
The dimensioning system performs self-calibration by automatically generating error models from measured objects and storing them in a library. The system then uses these self-generated models to correct subsequent measurements, eliminating the need for manual calibration while maintaining accuracy and preserving high measurement speed
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
This approach improves measurement accuracy, precision, flexibility, and speed by correcting errors associated with dimensioning systems, allowing for a wider variety of objects to be measured with reduced setup constraints.
Implementation Method 1
capturing an image of the projected light pattern that is reflected
Data Source
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AI summary
Methods to improve the accuracy of non-contact measurements of an object's dimensions using a dimensioning system are disclosed. The methods include a method for creating a mathematical model (i.e., error model) based on an observed correlation between errors in an estimated dimension and the characteristics of the measurement used to obtain the estimated dimension. These error models may be created for various dimensions and stored for future use. The methods also include a method for using the stored error models to reduce the error associated with a particular dimensioning-system measurement. Here an error model is used to create an estimated error. The estimated error is then removed from the estimate of the dimension to produce a final estimate of the dimension that is more accurate.