3D Data Acquisition Under Timing Constraints
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Solution Overview
Problem
Conventional 3D scanning systems face challenges in capturing complete views of objects moving on conveyor systems due to physical and temporal constraints, such as limited camera placement and varying object arrival rates, which hinder the acquisition of comprehensive 3D data for defect detection and analysis.
Innovation Solution
A system comprising multiple camera groups with overlapping fields of view, coordinated by a processor and a server, captures and combines partial 3D models from multiple viewpoints to generate a comprehensive 3D model of objects, using depth cameras and invisible light cameras to detect defects and adapt capture quality based on buffer occupancy and arrival rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple camera groups capture images simultaneously to improve data completeness, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system divides the imaging task into multiple camera groups, each responsible for capturing images of specific portions of objects at different locations along the conveyor. This segmentation allows simultaneous capture operations while managing complexity through modular organization of camera groups with overlapping fields of view.
Solution Approach 2:
Multiple camera groups are merged into a coordinated system that captures images from different viewpoints simultaneously. The processor combines images from all camera groups to reconstruct complete 3D models, achieving comprehensive object coverage that would be impossible with a single camera system.
2Productivity
If the system captures images at high frame rates to maintain throughput, then productivity is improved, but buffer occupancy management becomes more difficult
Solution Approach 1:
The system performs preliminary actions by capturing images at high frame rates before processing completes. The processor continuously acquires images and maintains buffers with captured data, preparing for subsequent processing operations. This allows the system to maintain high throughput while managing buffer occupancy through proactive data collection rather than reactive processing.
Solution Approach 2:
The system implements feedback mechanisms where the processor monitors buffer occupancy and adjusts capture operations accordingly. When buffers approach capacity, the system modulates frame rates or prioritizes processing of existing buffer data, creating a closed-loop control system that balances throughput with buffer management.
3Adaptability or versatility
If the conveyor moves at non-uniform speed causing variable object arrival rates, then adaptability is improved, but timing constraints on data acquisition worsen
Solution Approach 1:
The system dynamically adjusts its operation based on real-time conditions. The processor monitors object arrival rates and conveyor speed variations, modulating image capture frame rates and processing priorities accordingly. This dynamic adaptation allows the system to maintain data acquisition timing constraints despite non-uniform conveyor movement and variable object arrival patterns.
Solution Approach 2:
The system performs preliminary image capture at high frame rates before processing occurs. By buffering captured images and preparing them in advance, the system creates a time buffer that accommodates variable conveyor speeds and object arrival rates. This preliminary action ensures that data acquisition timing constraints are met even when conveyor operations are non-uniform.
Data Source
AI summary
A system for acquiring three-dimensional (3-D) models of objects includes a first camera group including: a first plurality of depth cameras having overlapping fields of view; a first processor; and a first memory storing instructions that, when executed by the first processor, cause the first processor to: control the first depth cameras to simultaneously capture a first group of images of a first portion of a first object; compute a partial 3-D model representing the first portion of the first object; and detect defects in the first object based on the partial 3-D model representing the first portion of the first object.