Multi-Intelligent Vehicle Cooperative Formation Control Method based on Visual Navigation

Abstract

There are many path information noises in the traditional multi-agent vehicle cooperative formation control method, which leads to poor dynamic stability. Use the image capture card in the visual navigation system to obtain the path information of multiple intelligent vehicles, enhance the image quality, extract the edge of the path, obtain the complete path feature, calculate the expected speed and expected position of the target intelligent car, and perform it on the original control protocol Improved to realize the cooperative formation control of multiple intelligent vehicles. The experimental results show that the designed multi-agent vehicle cooperative formation control method based on visual navigation has a timely and effective response to direction and acceleration, and the speed consistency is maintained at a high level, which shows that the dynamic steady-state performance of the control method has been improved.