Suction Gripper Pressure Sequencing for Pick Quality Detection
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Solution Overview
Problem
Existing sorting systems lack an efficient mechanism to evaluate the success or failure of pick operations by diverting mechanisms, particularly in complex systems with multiple mechanisms and objects with non-uniform surfaces.
Innovation Solution
The implementation of a pressure sequence analysis system that correlates the pressure of airflow through a gripper mechanism over time with representative pressure sequences to determine pick quality, combined with a machine learning approach to optimize pick locations and improve capture success rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a vacuum-based suction gripper mechanism is used to perform pick operations on objects with non-uniform surfaces, then the ability to capture objects is improved, but the difficulty of detecting and measuring pick quality increases
Solution Approach 1:
The system implements feedback by monitoring pressure sequences during pick operations and using this information to evaluate pick quality. The pressure data provides real-time feedback on whether a pick operation was successful, enabling the system to learn from outcomes and improve future decisions.
Solution Approach 2:
The patent replaces direct mechanical observation of pick quality with pressure sensing and machine learning analysis. Instead of mechanically detecting whether an object was successfully picked, the system uses pressure sequence analysis combined with ML models to infer pick quality, simplifying the detection mechanism.
2Productivity
If multiple diverting mechanisms and vision systems are deployed to handle complex sorting tasks, then the productivity of the sorting system is improved, but the device complexity increases
Solution Approach 1:
The patent creates a universal pick quality evaluation system that works across multiple diverting mechanisms and object types. The pressure sequence analysis approach and machine learning models are designed to be mechanism-agnostic and object-agnostic, allowing the same evaluation framework to be applied throughout the entire sorting system regardless of the specific mechanism or object being handled.
3Measurement precision
If pressure sequence analysis is implemented to evaluate pick quality, then the measurement precision of pick operation outcomes is improved, but the use of energy by the system increases
Solution Approach 1:
The system uses the existing vacuum airflow that is already required for the pick operation itself to provide the pressure monitoring function. The same vacuum system that performs the picking also provides the pressure data for evaluation, so no additional energy-consuming sensors or separate monitoring systems are needed.
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 solution enables accurate evaluation of pick operations, improves the success rate of object captures, and facilitates the identification of optimal pick locations, leading to enhanced performance and efficiency in material sorting systems.
Implementation Method 1
A vacuum-based suction gripper mechanism is used to perform pick operations on target objects
Implementation Method 2
A pressure meter is configured to record a pressure sequence associated with the pressure of the vacuum airflow through the suction gripper mechanism
Data Source
AI summary
Pick quality determination is disclosed, including: using a pressure meter to sense a pressure associated with an airflow through a gripper mechanism of a diverting mechanism over time during a pick operation on a target object; storing the sensed pressure associated with the airflow through the gripper mechanism over time as a pressure sequence associated with the pick operation on the target object; and correlating the pressure sequence with representative pressure sequences associated with corresponding pick quality types to determine whether the pick operation on the target object was successful or not.