Control System Of AGV Intelligent Car In Complex Environment

With the development and maturity of modern industrial automation technology,more and more researchers have turned their research direction to machine intelligence.AGV(Automatic Guided Vehicle)has been widely used in the direction of automation because of its high intelligence,environmental adaptability,reliability and safety.Based on the project requirements,this topic uses the Android terminal as the core of the AGV control system,studies the staircase environment information acquisition method and control scheme,and designs and implements the AGV car control system with real-time control.First of all,this article conduct a demand analysis and feasibility analysis of the AGV car control system.On this basis,the overall plan of the system is designed.The control system is divided into environmental data acquisition,path recognition and following control,automatic turning,communication mechanism,etc.Secondly,this paper studies the path recognition and following control schemes.After acquiring the staircase environment information through the camera and pre-processing,the image processing technology is used to segment and identify the path position information.After obtaining the straight line equation representing the path,A new control scheme based on deflection angle and offset distance is proposed.Next,the system of turn control method is studied,and a recognition method based on the monocular camera's visual ranging algorithm and the car of position judgment is proposed,which can accurately measure the distance between the car and the wall,with a ranging error of 1-2cm,And then make the corresponding action decision based on the current position of the car.Finally,the software and hardware platform of the system design is built,the communication method used by the system is designed,the Wi Fi and Socket technology are used to communicate the system with the small workshop,and the real-time control of the AGV car is realized.The system can control the car to drive normally in complex environment in real time.