Real-time path planning of factory car based on image processing and Dijkstra algorithm

Tracking cars are widely used in factories. However, there are relatively big limitations to tracking cars. The tracking cars can only walk according to the line drawn in the factory and cannot find the shortest distance between two points, which leads to a reduction in efficiency. To solve the phenomenon of frequent detours sometimes appearing in tracking cars, a solution is designed in this paper. In the case of the obvious gray level difference between the factory floor and the obstacles. A camera is used on the ceiling of the factory to take pictures at regular intervals and then pass the photos to the local segment of the computer. The Python program automatically reads the pictures and processes the pictures using the Canny operator. After processing by the Canny operator, the Dijkstra algorithm is used to design the shortest path between the starting position and the ending position of the car in this paper. In this way, a method to find the shortest path is finally obtained. After obtaining the shortest path for automatic cars, TCP/IP is used to transmit the planned path to the cars. This research can greatly improve the working efficiency of the car in the factory.