How the robot handles the problem of narrow aisles and obstructed vision in high-level storage applications. The connection of pallets, cages, shelves and other details greatly test the flexibility of unmanned forklift technology.
How can it be better?
Improving the adaptability and accuracy of unmanned forklifts, as well as reducing the cost of transformation in complex working conditions, has always been the demand of application companies, and it is also a difficult point for AGV companies to overcome with technology.
The first is strong ease of use: Compared with other navigation methods, visual navigation can extract semantic information from the environment, and has comprehensive three-dimensional visual perception, which can reduce the blind spots of robots, so it is more able to adapt to the needs of customers in routine use. Complicated scenes, such as racks and pallets that are deformed due to long-term use; super-boards for a large proportion of goods; rapid increase in handling capacity in a short period of time; vehicle scheduling in small spaces, etc.
Safety and stability: To achieve “machine substitution” for high-position forklift operations, safety must be the first step. After all, if the blind spots of the machine are ignored, safety accidents may occur. The high-mounted forklift AGV with 3D vision has rich information and stable navigation. When avoiding obstacles, it can not only stop and bypass obstacles, but also avoid obstacles at high altitude and negative scale (detect potholes), which is not possible with lidar. .
Relying on its strong growth and explosive power after years of deep cultivation of visual navigation technology, the future robot will not only complete the world’s first unmanned transformation of a high-position reach forklift, but also challenge the most difficult 4 layers in the current unmanned palletizing field. The precise stacking technology of the above baskets has been practically applied in the unmanned storage solution project of a giant auto parts manufacturer in South China.
Due to the obvious benefits of the stacking of cages in the first phase, the unmanned handling of automobile tires in the second phase followed one after another. The biggest difficulty of this project is that when reaching the 4-6th layer stack, the manual forklift stacking is inaccurate, the operation efficiency drops sharply, and the unsafe factor increases. When designing the solution, the robot will invest in a 9-meter stack in the future. VisionNav’s forward-moving unmanned forklift takes an average of 15 minutes for each process to maintain stable operation efficiency within the scope of 7*24H.
It is reported that the vision-guided unmanned forklift truck series of future robots has won market acclaim as soon as it was launched. So far, more than 150 different baskets and cages have been accurately identified and stacked independently, covering logistics, bonded, fast-moving consumer goods, etc. Unmanned pick-up and release projects for domestic middle- and high-rise warehouses of leading companies in multiple fields.
From this point of view, the application of visual navigation forklift AGV in high-position warehouses will be of great benefit.