Pallet Position Detection Using RFID and Lidar for Truck Unloading
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Solution Overview
Problem
Existing methods for unloading pallets from trucks using unmanned forklift vehicles face challenges in accurately identifying and positioning various types of pallets, especially when pallets are deformed or of unknown types.
Innovation Solution
A detection apparatus and method that utilizes an RFID tag or QR code to read pallet information and a Lidar sensor to detect a reflector on the pallet, allowing for accurate identification and positioning of pallets, regardless of type or deformation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a camera vision-based method is used to identify pallet information or position, then the system can attempt to recognize various pallet types, but some pallet types may not be recognized and deformation of pallet portions leads to lower recognition rate
Solution Approach 1:
The patent introduces RFID tags and QR codes as intermediary information carriers attached to pallets. These markers serve as reliable intermediaries that convey pallet information without being affected by pallet deformation or visual appearance variations. The detection apparatus reads information from these markers rather than attempting to recognize pallet characteristics directly, thereby ensuring high reliability across all pallet types.
Solution Approach 2:
The patent replaces the mechanical vision-based recognition system with an electromagnetic field-based reading system. Instead of using cameras to visually analyze pallet characteristics (which fails with deformed or unknown pallet types), the system uses RFID readers and QR code scanners to read information from electronic markers. This substitution eliminates the reliability issues associated with visual recognition while maintaining versatility.
2Extent of automation
If an unmanned forklift vehicle is used to unload pallets from trucks, then automation level increases, but accurate identification and positioning of various pallet types becomes more difficult
Solution Approach 1:
The patent applies preliminary action by pre-attaching RFID tags and QR codes to pallets before they are loaded onto trucks. These markers contain predetermined information about pallet identity, size, and position. When the unmanned forklift approaches, the detection apparatus quickly reads this pre-encoded information, eliminating the need for complex real-time analysis and enabling accurate, automated position detection.
Solution Approach 2:
The patent introduces detection markers (RFID tags and QR codes) as intermediaries that facilitate communication between the unmanned forklift system and the pallets. These markers provide structured, machine-readable information that the automated system can reliably interpret, making pallet detection and positioning straightforward tasks for the unmanned vehicle regardless of pallet type or condition.
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 reliable and accurate detection of pallet information and position, facilitating efficient unloading of pallets by unmanned forklift vehicles, regardless of pallet type or condition.
Implementation Method 1
The pallet information marker may be at least one of a Radio Frequency Identification (RFID) tag and a Quick Response (QR) code, and the information detector may include at least one of an RFID reader configured to read the RFID tag
Implementation Method 2
The pallet position marker may include a reflector configured to reflect a laser, and the position detector may include a Lidar sensor configured to sense the laser
Data Source
AI summary
A pallet position detection apparatus is provided. The detection apparatus and method checks information on a pallet disposed on a vehicle by recognizing an Radio Frequency Identification (RFID) tag or a Quick Response (QR) code attached to the truck, and recognizes an exact position of the pallet by detecting a reflector positioned on the pallet by a Lidar sensor, and unloads the pallet from the truck using an unmanned forklift vehicle based on the recognized position of the pallet.