Forklift Navigation Using Human-Visible Warehouse Markings
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Solution Overview
Problem
Existing navigation systems for industrial trucks require dual intervention, with manual installation of markings and data entry, leading to errors and limitations in mixed operation between manual and automated modes, as they fail to utilize existing visible information intended for humans.
Innovation Solution
The method employs an optical sensor, such as a camera, to detect and categorize existing floor markings, traffic signs, and shelf inscriptions, using context recognition to generate navigation instructions and control commands, eliminating the need for special markings and reducing error-prone interventions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If special markings and radio beacons are installed for automated navigation, then automated navigation capability is improved, but device complexity and cost increase
Solution Approach 1:
The patent makes existing warehouse markings (footpath markings, lane lines, shelf labels) serve dual purposes: they continue to guide manual operators while simultaneously providing navigation data for automated trucks through optical sensing. This eliminates the need for separate specialized markings, reducing system complexity while maintaining automated navigation capability.
Solution Approach 2:
The system uses the warehouse's existing visual infrastructure (markings and signs already present for human operators) to automatically navigate the truck. The optical sensor captures visible information, and the data processing device extracts navigation instructions directly from these existing markings, allowing the system to self-navigate without requiring additional specialized infrastructure.
2Reliability
If dual intervention (manual marking installation and data entry) is required, then navigation information can be provided, but error probability increases
Solution Approach 1:
The patent replaces the manual mechanical process of data entry with an automated optical sensing and image processing system. The optical sensor captures markings, the data processing device performs context recognition and extracts navigation information automatically, eliminating human intervention and associated errors in data transcription.
Solution Approach 2:
Instead of manually entering navigation data, the system creates an optical copy of the existing warehouse markings through the optical sensor. The data processing device then extracts and processes this copied visual information directly, maintaining accuracy while eliminating the error-prone manual data entry step.
3Extent of automation
If warehouse is designed for automated operation with special markings, then automated navigation is improved, but manual operation capability deteriorates
Solution Approach 1:
The patent enables markings to serve multiple functions simultaneously: they guide manual operators visually while providing navigational data for automated trucks. This universal approach allows the same warehouse environment to support both manual and automated operations without requiring separate infrastructure, thereby maintaining adaptability and versatility.
Solution Approach 2:
Instead of designing specialized markings for automated trucks that would exclude manual operators, the patent inverts the approach by making existing human-oriented markings serve automated navigation purposes. This reversal allows automated trucks to utilize the same visual infrastructure that manual operators rely on, enabling mixed operation capability.
4Measurement precision
If context recognition is used to evaluate visible information, then navigation accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent applies context recognition selectively to specific types of markings (footpath markings, lane lines, shelf labels, traffic signs) rather than attempting to process all visual information uniformly. The data processing device is configured to recognize and extract navigation instructions from these particular marking types, achieving high navigation accuracy while limiting processing complexity to relevant contexts.
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
Enables mixed operation of manual and automated industrial trucks by leveraging existing information, improving navigation accuracy and adaptability, and reducing the need for additional markings and data entry, thus enhancing operational efficiency and reducing errors.
Implementation Method 1
An optical sensor, with which visible information provided for people and placed in the operating area of the industrial truck for operators can be recorded
Data Source
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AI summary
The invention relates to a method for navigating a forklift (10) with an optical sensor (12) for detecting information in the operating area of the forklift (10) and a data processing unit for evaluating this information and generating navigation instructions and/or control commands for navigating the forklift (10), as well as a device for carrying out the method. It is proposed that the optical sensor (12) detects information (1, 2, 3, 4, 6, 9, 14, 15) visible to humans and located in the operating area of the forklift for operators, and that the data processing unit uses context recognition to generate the navigation instructions and/or control commands for navigation from this information.