Object Detection Data Selection for Conveyor Robot Grasping
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Solution Overview
Problem
Existing robot systems that detect objects on conveyor devices face issues with invalidating detection results after the first acquisition, leading to inefficiencies in object recognition and handling.
Innovation Solution
A detection system that includes a detection unit, a work-data creation unit, and a work-data storage unit, which creates and selects work data based on indices such as position and quality-related scores to improve detection accuracy and reliability by choosing the most accurate data from multiple detections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If detection results are invalidated after the first acquisition, then the system simplifies data management, but detection accuracy and reliability deteriorate
Solution Approach 1:
The patent applies parameter changes by introducing an evaluation index that quantifies detection quality. Instead of简单地 invalidating subsequent detections, the system evaluates each detection result using parameters such as focus accuracy, illumination conditions, and detection confidence scores. This allows the system to select the highest quality detection result among multiple acquisitions, thereby improving detection accuracy while maintaining manageable data complexity through structured evaluation criteria.
Solution Approach 2:
The patent implements feedback mechanisms by continuously evaluating detection results and using this information to guide subsequent detection operations. The evaluation index provides feedback on detection quality, allowing the system to adjust detection parameters, select optimal results, and improve overall detection reliability. This feedback loop enables the system to learn from multiple detection attempts and consistently produce accurate results.
2Reliability
If multiple detection results are stored, then detection reliability improves, but data storage requirements and processing complexity increase
Solution Approach 1:
The patent applies the extraction principle by selectively storing only the essential elements of detection results based on evaluation indices. Instead of storing complete detection datasets, the system extracts and stores only the high-quality detection results that meet predetermined criteria. This approach maintains detection reliability by ensuring stored data is of proven quality while significantly reducing storage requirements by eliminating redundant or low-quality data.
Solution Approach 2:
The patent implements discarding and recovering by systematically evaluating multiple detection results and discarding those that do not meet quality standards. The system recovers and retains only the optimal detection results for storage and subsequent use. This process ensures that stored data maintains high reliability while minimizing storage volume by actively filtering out unnecessary data through the evaluation index mechanism.
3Speed
If the latest detection data is always used, then processing speed improves, but detection accuracy may deteriorate due to poor detection conditions
Solution Approach 1:
The patent applies preliminary action by evaluating detection results before they are selected for use. The evaluation index assesses detection quality in advance, identifying suitable results that meet predetermined accuracy criteria. This preliminary evaluation ensures that only high-quality detection data is selected, preventing the use of inaccurate data even when it is the most recent. The system prepares evaluation criteria beforehand and applies them systematically to maintain both speed and accuracy.
Solution Approach 2:
The patent uses feedback mechanisms to balance speed and accuracy by continuously monitoring detection quality through evaluation indices. When detection conditions are poor, the feedback system identifies this through lowered evaluation scores and adjusts selection criteria accordingly, preventing the automatic selection of low-quality rapid detections. This feedback loop allows the system to maintain processing speed while ensuring that accuracy thresholds are met before data is used.
Data Source
AI summary
A detection system includes a first detection apparatus that detects an object that is being moved, within a predetermined detection region, a number of times, a work-data creation device that creates, every time the first detection apparatus detects the object, work data having a first data element that indicates at least a position of the object obtained by the first detection apparatus and a second data element that includes at least an index related to the object and obtained at the time of the detection, and a work-data storage unit that stores the work data created by the work-data creation means. The work-data storage unit selects, as the work data that should be stored, one of the work data that is newly created for the object and the work data for the object that has been stored by the work-data storage unit, on the basis of the index.