Automatic Mode Switching for Single-Sensor Dimensioning
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Solution Overview
Problem
Existing dimensioning systems face challenges in accurately measuring irregularly shaped objects and multiple objects, often requiring multiple sensors or time-consuming multiple view measurements, which are costly and inefficient.
Innovation Solution
A single sensor dimensioning system that automatically switches between three modes to capture the necessary views for dimensioning, using a pattern projector and range camera to calculate the minimum bounding box (MVBB) based on object characteristics, such as cuboids, objects with obtuse angles, and those with protrusions or overhangs, allowing for efficient and accurate measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are used to measure irregular objects, then measurement accuracy is improved, but device cost and complexity increase
Solution Approach 1:
The system dynamically switches between different measurement modes (single view, two views, three views) based on object characteristics detected during scanning. This allows the system to adapt the complexity of measurement to the actual needs of each object, using multiple views only when necessary for irregular objects while maintaining single-view efficiency for regular objects.
Solution Approach 2:
The system changes the measurement parameter (number of views captured) based on detected object features such as obtuse angles and protrusions. By analyzing geometric parameters of the object and automatically determining the required number of views, the system optimizes between measurement accuracy and operational efficiency.
2Measurement precision
If multiple views are always captured for all objects, then measurement accuracy for irregular objects is improved, but measurement time increases
Solution Approach 1:
The system dynamically determines the number of views to capture based on real-time analysis of object geometry. Regular objects (cuboids without protrusions) are measured in a single view, while objects with detected irregularities (obtuse angles, protrusions) automatically trigger multi-view capture, optimizing measurement time while ensuring accuracy when needed.
Solution Approach 2:
The system performs preliminary detection of object characteristics (such as identifying obtuse angles and protrusions) before final dimension calculation. This preliminary analysis allows the system to determine upfront whether additional views are necessary, avoiding unnecessary measurement time for objects that can be accurately measured from a single view.
3Device complexity
If a single sensor is used to reduce cost, then device complexity is reduced, but the ability to measure irregular objects accurately is worsened
Solution Approach 1:
The system compensates for the limitations of a single sensor by capturing objects from multiple dimensional perspectives (multiple views/angles). When irregular features are detected, the system automatically acquires additional views to ensure complete geometric information is captured, allowing a single sensor to achieve multi-sensor measurement accuracy through multi-view data fusion.
Solution Approach 2:
The system uses feedback from initial object scanning to automatically determine whether additional views are required. By analyzing detected features (obtuse angles, protrusions) and triggering appropriate measurement modes, the single sensor system adapts its measurement strategy to maintain accuracy comparable to multi-sensor systems while avoiding their complexity and cost.
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
Enables quick, accurate, and cost-effective measurement of various shaped objects by determining the optimal number of views needed, reducing measurement errors and operational costs while ensuring certification in commerce.
Implementation Method 1
The dimensioning system may sense an object by projecting a light pattern (i.e., pattern) into a field-of-view
Implementation Method 2
The dimensioning system can capture an image of the reflected light-pattern and analyze the pattern distortions in the captured image to compute the 3D data necessary for dimensioning
Data Source
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AI summary
Dimensioners and methods for dimensioning an object includes capturing, using a dimensioning system with a single sensor, at least one range image of at least one field-of-view, and calculating dimensional data of the range images and storing the results. Wherein, the number of views captured of the object is automatically determined based on one of three modes. The first mode is used if the object is a cuboid, or has no protrusions and only one obtuse angle that does not face the point of view, where it captures a single view of the object. The second mode is used if the object includes a single obtuse angle, and no protrusions, where it captures two views of the object. The third mode is used if the object includes a protrusion and/or more than one obtuse angle, overhang, protrusion, or combinations thereof, where it captures more than two views of the object.