Palletizer Vision Control for Obstacle Detection and Stop Signals

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Solution Overview

Problem

Existing palletizers, particularly layer pickers, experience inefficiencies during handling processes due to inadequate item pickup, leading to potential malfunctions and hot downtimes.

Innovation Solution

A computer-implemented method using machine-learning to analyze image data from cameras, detecting obstacles that may cause malfunctions, and generating control signals to stop the handling process, thereby preventing errors and reducing downtime.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If traditional palletizer operation is used, then the handling process can proceed continuously, but malfunctions occur due to inadequate item pickup detection, leading to hot downtimes

Engineering Contradiction:

Improvehandling process reliabilityVSAvoidhandling process efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system performs preliminary detection of items to be handled using image capture and machine learning analysis before the handling process begins. This allows obstacles that could cause malfunctions to be identified in advance, enabling preventive stopping of the process before failures occur, thus improving reliability without sacrificing productivity

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements a feedback loop where image data from the handling process is continuously analyzed by a machine learning model, and control signals are generated in real-time based on the analysis results. This closed-loop feedback enables dynamic adjustment of the handling process to prevent malfunctions while maintaining continuous operation, resolving the contradiction between reliability and productivity

Inventive Principle:

Principle #23Feedback

2Reliability

If machine learning analysis is added to detect obstacles, then handling process reliability improves, but system complexity increases

Engineering Contradiction:

Improvehandling process reliabilityVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system replaces complex mechanical detection mechanisms with an optical imaging system combined with machine learning analysis. Instead of using multiple sensors or complex mechanical probes to detect item characteristics, the system uses image capture and computational analysis, which reduces mechanical complexity while improving detection reliability

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The machine learning model acts as an intermediary between the image capture system and the control system. It processes image data and translates it into meaningful obstacle detection results, simplifying the overall system architecture by providing a clear interface between sensing and actuation components

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS20250178200A1Method for Operating a Palletizer

Publication Date: 2025.06.05 BUYERS SUPPLY CHAIN DK A S

AI summary

The present invention relates to a computer-implemented method of for operating a palletizer, comprising: receiving image data, using at least one camera, of at least one item intended to be handled by the palletizer in a handling process; analyzing, using a machine-learning model, the received image data; determining, using the machine-learning model, that an obstacle may cause a malfunction of the handling process; and generating a control signal for instructing the palletizer to stop the handling process.