Multiway robot: Differentiated Scene Technology to Fully Promote the Intelligent Construction of Warehousing and Logistics

In November 2020, Multiway Robot announced its latest progress in technical scenarios: "high-level access to goods", "cage stacking", "pallet attitude recognition", and "high-precision positioning" application scenario technologies. Among them, "pallet attitude recognition technology" is the first pallet recognition technology in the industry that is truly used in the industrial field, which solves the problem of large position offset and angle offset of unmanned forklift AGV docking pallets.

1. Unmanned forklift AGV pallet gesture recognition technology

According to the introduction of Mawei Robot R&D Center, Mawei's "tray attitude recognition technology" can achieve a pallet offset of ±30 cm and an angle of ±30 degrees. This technology is one of the breakthroughs in the application scenarios of AGV technology of Mawei unmanned forklift trucks.

Based on an excellent architecture with a deep understanding of the industry, millimeter-level high-precision positioning and navigation, the industry's highest speed driving control, large-scale robot cluster scheduling and machine vision and other technical advantages, it has industry-leading technical solutions and products.

2. Unmanned forklift AGV high-level storage and retrieval technology

At present, the scenarios of unmanned forklift AGV in warehousing include: beam racks, drive-in racks, narrow aisle racks, double-depth racks, shuttle racks and other intensive storage scenarios. "It's very cold at high places", as the height of the unmanned forklift AGV increases during stacking operations, it has higher requirements for the stability and accuracy of the lifting of the fork arm. The micro-forward MW-R unmanned forklift can realize fully automatic unmanned handling of forklifts and goods in and out of the warehouse. It is mainly used for horizontal handling of production lines and warehouses, vertical loading and unloading of shelves and loading and unloading of goods. The rated load is 2.0T, and the maximum operating speed is 3.0m/s, the highest lift is 11.5m, and the manual/automatic driving mode can be switched with one key.

And the implementation does not need to change the on-site environment to achieve precise positioning of the unmanned forklift AGV, with a positioning accuracy of ±5mm; the unmanned forklift AGV body is equipped with an advanced 3D vision module, which has the functions of vehicle detection and shelf detection, and can be adapted to the vehicle and the vehicle. 

3. Unmanned forklift AGV cage stacking technology

"Cage stacking technology" is a huge test for the intelligence and operation accuracy of the unmanned forklift AGV. Momobot has always attached great importance to the combination of visual navigation technology and unmanned forklift AGV. With its unique technical route and strong growth and explosive power in the later period, Momorobot has challenged the difficulty of stacking more than 3 layers of material cages for current unmanned forklifts, and has achieved accurate and accurate results. In terms of environmental perception, the depth camera is used to perceive the surrounding environment in real time, and the positioning and AI technology are integrated to dynamically construct the running trajectory of the unmanned forklift, and finally achieve accurate stacking without errors.

4. Unmanned forklift AGV high-precision pick and place goods

This technology is mainly used in scenarios such as logistics connection between production lines, forklifts and production line goods, high value of goods, and smooth handling. For unmanned forklifts to pick and place goods back and forth, the AGV can achieve a positioning accuracy of ±5mm at one time, which is much higher than the industry requirement of ±10mm to ensure that the goods will not be damaged due to accuracy problems during the docking and handling process.

At the same time, based on the real-time ontology state feedback, the micro unmanned forklift can combine the center of mass dynamics model to construct the optimization problem. Different from other unmanned forklift AGV manufacturers that do repetitive motions after pre-designed rules, Momobot pays more attention to the research on the conscious and judgmental autonomous characteristics of unmanned forklift AGVs. The purpose is to work in a dynamic environment with great uncertainty, which can realize the robot's path planning, collaborative docking, cluster scheduling, and complete tasks autonomously.