Shelf Transport Vehicle Position Recognition in Crowded Warehouses
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Solution Overview
Problem
Unmanned shelf transport vehicles struggle to recognize and track the positions of multiple shelves within their measurement range, leading to failures in navigation and alignment, especially when shelves are dispersed or surrounded by other vehicles.
Innovation Solution
A shelf transport system equipped with a distance sensor, shelf leg candidate detection module, arrangement calculation module, excess/deficiency calculation module, arrangement determination module, and movement destination determination module, which allows the vehicle to calculate and determine the correct shelf arrangement even in crowded environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the unmanned shelf transport vehicle uses a distance sensor to measure the position of shelves, then it can detect shelf locations, but it fails to recognize and track positions when multiple shelves are within the measurement range
Solution Approach 1:
The patent segments the shelf recognition process into distinct modules: a shelf leg candidate detection module that identifies individual shelf legs, a shelf arrangement candidate calculation module that generates possible arrangements, and a shelf arrangement determination module that selects the correct arrangement. This segmentation allows the system to handle multiple shelves by processing them in discrete steps rather than attempting to recognize all shelves simultaneously, resolving the contradiction between measurement precision and device complexity.
2Adaptability or versatility
If the unmanned shelf transport vehicle operates in a warehouse with dispersed shelves, then it can access more shelves, but workers are required to align shelves manually because the vehicle cannot grasp their positions
Solution Approach 1:
The patent applies preliminary action by having the shelf arrangement candidate calculation module generate multiple possible shelf arrangements before the vehicle attempts to align with them. The shelf arrangement determination module then evaluates these pre-calculated candidates to identify the correct arrangement. This preliminary calculation and evaluation process enables the vehicle to automatically determine shelf positions without manual alignment, enhancing both adaptability to dispersed shelves and ease of automatic operation.
3Reliability
If the unmanned shelf transport vehicle relies on floor markers for position recognition, then it can track its path, but it fails to recognize and track position when moved out of the path due to tire slip or surrounded by other vehicles
Solution Approach 1:
The patent introduces shelf legs as an intermediary reference object for position tracking. Instead of relying solely on floor markers that may become inaccessible when the vehicle slips or is surrounded, the vehicle uses the distance sensor to detect shelf legs as a mediator to re-establish its position. The shelf leg candidate detection module identifies these intermediary shelf legs, and the subsequent arrangement determination process uses them as reference points to recover the vehicle's position, thereby improving reliability without significantly increasing device complexity.
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 the unmanned shelf transport vehicle to accurately recognize and align multiple shelves by determining the correct arrangement and movement path, even when shelves are not initially aligned, and allows it to recover its own position if lost.
Implementation Method 1
A first robot includes: a measurement part measuring the reflection light intensity of an object
Data Source
AI summary
A shelf transport system comprising a shelf transport vehicle transporting a shelf having shelf legs, the shelf transport vehicle comprising: a distance sensor measuring a distance to an obstacle; a shelf leg candidate detection module detecting shelf leg candidates, which are candidates for the shelf legs; a shelf arrangement candidate calculation module calculating shelf arrangement candidates, in each of which the shelf is virtually arranged on the shelf leg candidates; an excess/deficiency calculation module calculating, for each of the shelf arrangement candidates, the excessive and the deficient number of shelf leg candidates; a shelf arrangement determination module determining a shelf arrangement from among the shelf arrangement candidates based on the excessive and the deficient number of shelf leg candidates; and a movement destination determination module determining a shelf to which the shelf transport vehicle is to be moved based on the shelf arrangement.