Camera Scanning System Optimization for Robotic Item Identification
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Solution Overview
Problem
Conventional approaches for deploying camera devices for item identification in facilities are complex, time-consuming, and resource-intensive, often resulting in inefficient placement and configuration that can lead to high rates of mis-identification.
Innovation Solution
The optimization component evaluates various parameters of a camera-based scanning system, including image sensor, lens, illumination, and workcell parameters, to determine the optimal deployment and configuration of camera devices, minimizing the number of devices needed to achieve a target scan volume with high reading accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional approaches are used for deploying camera devices, then item identification can be performed, but the deployment process becomes complex and time-consuming
Solution Approach 1:
The system changes parameters such as camera placement locations, orientations, and field-of-view angles to optimize scanning performance. By adjusting these parameters systematically, the patent achieves reliable item identification while simplifying the deployment process through automated parameter optimization rather than manual configuration.
Solution Approach 2:
The system performs preliminary analysis to determine optimal camera deployment parameters before actual deployment. This includes pre-calculating placement locations, orientations, and field-of-view configurations to ensure accurate item identification from the start, avoiding complex adjustments during operation.
2Measurement precision
If more camera devices are deployed to improve scanning coverage, then reading accuracy increases, but resource consumption and system cost increase
Solution Approach 1:
Each camera device is configured to perform multiple functions by optimizing its field-of-view and placement to scan multiple items simultaneously. This multi-functionality allows fewer cameras to achieve the same reading accuracy that would otherwise require more devices, reducing resource consumption while maintaining precision.
Solution Approach 2:
The system transitions from considering only the number of cameras to optimizing three-dimensional parameters including placement height, horizontal position, and rotation angles. By utilizing spatial dimensions effectively, the patent achieves comprehensive scanning coverage with minimal devices, improving reading accuracy without increasing quantity.
3Area of stationary object
If camera devices are placed to cover maximum area, then scanning coverage improves, but identification accuracy decreases due to suboptimal positioning
Solution Approach 1:
Instead of uniform camera placement, the system applies local quality optimization by positioning each camera at specific locations and orientations tailored to the local scanning requirements. This ensures that each camera operates at optimal quality for its specific position, maintaining high identification accuracy across the entire coverage area.
Solution Approach 2:
The system dynamically adjusts camera parameters such as field-of-view angles, focal lengths, and placement positions based on real-time scanning requirements and item locations. This dynamic optimization ensures that coverage area and identification accuracy are simultaneously maximized by adapting to changing conditions rather than using fixed suboptimal configurations.
Data Source
AI summary
Systems and techniques for optimizing deployment of a camera scanning system in an environment for item identification are described. An example technique involves obtaining a first set of parameters of the camera scanning system and obtaining a second set of parameters of the environment. A third set of parameters of a predicted scan volume of the camera scanning system are determined based on the first set of parameters and the second set of parameters. At least one of the first or second sets of parameters is modified upon determining that the predicted scan volume satisfies a first predetermined condition. An indication of at least one of the first, second, or third sets of parameters is transmitted upon determining that the predicted scan volume satisfies a second predetermined condition.