Suction Cup Seal Quality Modeling for Robotic Picking

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Solution Overview

Problem

In product distribution centers, robotic systems face challenges in reliably picking and handling items of various shapes and sizes due to the lack of an effective method to determine optimal contact points for suction devices, leading to high failure rates and potential damage to items.

Innovation Solution

The implementation of a robotic control optimization system that uses a suction cup model to determine candidate contact points on an item based on its surface geometry, calculates an estimated seal quality metric using a three-dimensional spring lattice, and selects the optimal contact point to enhance the robotic picking arm's effectiveness and efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If a robotic picking arm uses a suction device to retrieve items, then automation extent is improved, but reliability deteriorates due to high failure rates in picking attempts

Engineering Contradiction:

Improveautomation of item retrievalVSAvoidpicking success rate

Core Design Contradiction:

Extent of automationVSReliability

Solution Approach 1:

The system performs preliminary analysis of the item's three-dimensional surface model before the picking attempt to identify optimal contact points and calculate seal quality metrics. This advance preparation allows the robotic arm to select the best suction contact point, thereby improving picking success rate while maintaining automation.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system uses feedback from the three-dimensional surface model analysis and seal quality metric calculations to continuously improve picking decisions. By evaluating multiple candidate contact points and selecting the optimal one based on calculated metrics, the system increases reliability while maintaining automated operation.

Inventive Principle:

Principle #23Feedback

2Productivity

If the robotic system attempts to pick items without optimizing contact points, then productivity is maintained, but reliability deteriorates due to dropped items

Engineering Contradiction:

Improvepicking speedVSAvoiditem retention

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system performs rapid preliminary analysis of the item's surface geometry and calculates seal quality metrics for multiple candidate contact points before the picking attempt. This pre-computation enables quick selection of the optimal contact point without significantly slowing down the picking process, thus maintaining productivity while improving reliability.

Inventive Principle:

Principle #10Preliminary action

3Device complexity

If the robotic system uses a simple picking method, then device complexity is reduced, but reliability worsens due to inability to handle various item geometries

Engineering Contradiction:

Improvepicking system complexityVSAvoidadaptability to item shapes

Core Design Contradiction:

Device complexityVSReliability

Solution Approach 1:

The system replaces complex mechanical adaptability with computational analysis. Instead of requiring physically adaptive grippers for different item shapes, the system uses three-dimensional surface modeling and seal quality metric calculations to determine optimal suction contact points, achieving high reliability across various item geometries while keeping the mechanical system relatively simple.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Ease of operation

If the robotic arm uses suction device without optimization, then ease of operation is improved, but reliability deteriorates due to high failure rate

Engineering Contradiction:

Improvesimplicity of picking operationVSAvoidpicking success

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The system performs self-analysis by automatically generating the three-dimensional surface model, identifying candidate contact points, and calculating seal quality metrics without external intervention. This self-service capability maintains ease of operation while dramatically improving reliability through optimized contact point selection based on computed metrics.

Inventive Principle:

Principle #25Self-service

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 approach significantly reduces failed picking attempts and improves the robotic picking arm's performance by identifying the strongest seal quality metric, ensuring reliable item retrieval and minimizing item damage.

Implementation Method 1

using a three-dimensional spring lattice to model deformation and contact between a suction device for a robotic picking arm and a candidate contact point of an item, such that potential energy across the three-dimensional spring-lattice is minimized

Methodology Applied

Scientific EffectElasticity: Elasticity

Data Source

PatentUS11654582B2Optimization-based spring lattice deformation model for soft materials

Publication Date: 2023.05.23 AMAZON TECH INC

AI summary

Techniques for controlling a robotic picking arm using estimated seal quality metrics. A plurality of candidate contact points for holding an item using a suction device of the robotic picking arm, based on captured images of the item and an n-dimensional surface model of the item. An expected seal quality metric for a first one of the candidate contact points, by processing the n-dimensional surface model of the item and physical properties of the suction device of the robotic picking arm. Based on the expected seal quality metric, embodiments can determine whether to retrieve the item from the storage container by holding the item at the first candidate contact point using the suction device of the robotic picking arm.