Introduction to AGV Unmanned Forklift Docking Methods: The Core Hub of Intelligent Logistics

 In smart manufacturing and intelligent logistics, AGV (Automated Guided Vehicle) unmanned forklifts have become core equipment for improving warehouse efficiency. Their value lies not only in their autonomous handling capabilities but also in their ability to integrate with various warehouse equipment and systems seamlessly. This article will provide a detailed analysis of the five typical integration methods for AGV unmanned forklifts, revealing how they achieve full-process logistics automation through technological integration.

 1. Connecting with The Conveyor Line

Technical Implementation:

The AGV identifies the position of the conveyor line through laser radar or visual sensors, and uses high-precision positioning technology (such as QR code navigation and SLAM laser navigation) to achieve a connection accuracy of ±10 mm. When the conveyor line transports materials to the designated node, the AGV automatically travels to the connection port and completes the transfer or release of materials through a lifting mechanism.

Application Scenarios:

• Production Workshop Line-Side Warehouse: The AGV interfaces with a roller conveyor line, real-time retrieving completed transmission assemblies from the production line and directly transferring them to the assembly line, reducing the 15% efficiency loss caused by manual transfer.

• Smart Sorting Centre: Interfaces with a cross-belt sorter, where the AGV automatically disassembles full pallet loads into small packages, boosting sorting efficiency to four times that of traditional manual sorting.

Core Advantages:

• Continuous Operation Capability: 24/7 uninterrupted docking eliminates rhythm interruptions caused by manual docking;
• Flexible Adaptability: Supports multiple conveyor line speeds (0.5–2 m/s), compatible with different production lines through software parameter adjustments.

2. Integration with Shelving Systems

Technical Implementation:

(1) Traditional Shelving (Flat Warehouse):

AGVs use side-shifting and forward/backwards tilting functions to precisely insert into the pallet holes at the bottom of the shelves (error ≤ 5 mm), and work with lifting mechanisms to complete goods storage and retrieval. Some models are equipped with robotic arm-style forks to accommodate shelves of different depths.

(2) Intelligent Three-dimensional Warehouse:

In conjunction with stackers and shuttles, AGVs handle front-end logistics, delivering materials to the entrance of the automated storage system's aisles. For example, a certain electrical manufacturing company successfully achieved automated material transfer and finished goods storage through the integration of AiTEN AGVs with the automated storage system, significantly improving production efficiency. 

 AiTEN Application Case:

3차원 창고 셔틀과 연계한 AGV를 통한 자재 자동 이송

3. Integration with Elevators/Lifts

Technical Implementation:

AGVs are deeply integrated with elevator control systems via wireless communication protocols, enabling full-process automation from ‘autonomous elevator call’ to ‘precise floor alignment’ to ‘safe entry and exit.’ Typical processes include:

1. When an AGV approaches an elevator, it identifies the elevator number via RFID tags or visual recognition and sends a call command.
2. Upon the elevator's arrival, the AGV uses a laser radar to scan the elevator floor's flatness, ensuring levelling error <3mm;
3. During entry/exit, the AGV continuously monitors obstacles inside the elevator car and initiates an emergency stop within 0.2 seconds in case of sudden incidents.

 AiTEN Application Case:

A new energy company needed to transport goods between floors, which was time-consuming and labour-intensive. They used the Dolphin Star APe15 transport robot to transport goods and load them into elevators, improving warehouse transport efficiency and intelligence, reducing labour costs, and ensuring accurate transport of goods.

 4. Integration with Collaborative Robots

Technical Implementation:

AGVs collaborate with robotic arms and palletising robots through a unified scheduling system (such as the RDS robot scheduling system):

• Material Handling Scenario: AGVs deliver fully loaded pallets to the collaborative robot workstation, where robotic arms automatically unload and assemble parts, while AGVs simultaneously remove empty pallets.
• Mixed-line production: In small appliance factories, AGVs deliver customised material combinations to different production lines based on production orders, collaborating with robots to achieve flexible production of ‘multiple varieties and small batches,’ reducing changeover time from 2 hours to 15 minutes.

Collaborative Advantages:

• Optimised Human-Machine Division of Labour: AGVs handle heavy-duty material handling, robots focus on precision operations, and personnel transition to process monitoring.
• Data Interoperability: Through the MES system, production progress is synchronised in real-time, and AGVs dynamically adjust material handling priorities to prevent material backlogs.

 5. Integration with WMS Systems

Technical Implementation:

AGVs seamlessly integrate with warehouse management systems (WMS) through API interfaces:

• Task Assignment: WMS automatically generates handling instructions based on inventory data (e.g., ‘Move the pallet from Shelf 3 in Zone A to Picking Position 5 in Zone B’), which are then assigned to the nearest AGV via the AGV scheduling system;
• Status Feedback: AGVs continuously transmit real-time data such as location, task progress, and battery level, enabling WMS to dynamically update inventory status and eliminate data errors caused by manual entry.
• Data analysis: By training algorithms using historical handling data, AGV path planning is optimised, reducing unnecessary travel distance by 30%.

Application Case:

Dolphin Star customised an efficient, intelligent handling solution based on the on-site environment and production requirements of a certain automotive parts manufacturing company. It adopted the lightweight and compact handling robot MP10s as the core equipment, and integrated it with AiTEN Robot's WCS equipment interface system, RDS scheduling system, and LMS location management system to achieve full-process automation. This resulted in a 50% increase in operational efficiency and a smoother production process.

물류 관리가 혼란스러운 자동차 공장의 창고 활용도를 30% 향상시킨 AiTEN의 맞춤형 솔루션

6. Conclusion

From a simple transport tool to an intelligent logistics hub, the evolution of AGV unmanned forklifts is essentially a history of upgrading connectivity capabilities. By deeply integrating with physical equipment and digital systems, AGVs are redefining the collaborative relationship between humans, machines, and objects, driving the transformation of warehouse logistics from a labour-intensive model to a technology-driven one. In the future, with the application of 5G and AI large models, AGVs will achieve autonomous decision-making and dynamic coordination in more complex scenarios, becoming the core infrastructure of smart manufacturing.

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