Is the visual navigation system applied to the agv car reliable?

The visual navigation system currently applied to the agv car was initially applied to the automated production line. In the visual navigation of unmanned vehicles, the technology used is to obtain visible light signals through cameras, and according to the simulated visual navigation system, functions that traditional electric hydraulic pallet trucks cannot do.

In addition to visual navigation, driverless AGV navigation now presents several navigation methods, namely: laser navigation, magnetic navigation, etc. Today, the world-renowned agv manufacturers have not done a complete visual navigation.

Visual navigation is different from other navigation methods. The biggest advantage of the visual navigation agv car is that there is no fixed reference. However, during the activity of the AGV trolley, the requirements for the accurate positioning of the vehicle and track components are getting higher and higher. Although the visual navigation system used on the automated assembly line can achieve an accuracy of 0.1mm, but based on the visual navigation AGV without a fixed reference, the positioning accuracy is usually not high (pure visual navigation system).

If the car visual navigation system wants to achieve higher positioning accuracy, in addition to visual navigation, other navigation is needed as an aid, and then try to use the visual system of fixed reference objects, so that positioning Accuracy and positioning accuracy are very good. Safety performance can be obtained.

In the long run, the development prospects of visual navigation systems are still very good. On the one hand, visual navigation is the closest approach to understanding human 'navigation and obstacle avoidance'. In addition to navigation, multi-cameras can also be used as inspections to record the details of AGV trolley operations. AGVs will eventually develop in the direction of artificial intelligence navigation.

The car does not have a visual navigation method with a fixed reference object, so it will be able to obtain a more convenient layout. Artificial intelligence navigation can completely solve the shortcomings of current navigation methods. In terms of hardware cost and maintainability, visual navigation has more advantages.

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