Petri Net Modelling and Motion Analysis of the Football Robot System

The football robotics competition has become one of the typical systems used in multi-robot research to study robot control, artificial intelligence and task allocation. The design of a football robot is a more integrated research module including robot design, visual information processing, and robot motion control. In this paper, a monocular global camera is used on the vision acquisition module to capture information within the football field in real time. Edge detection and feature point extraction are performed on the images after color recognition processing to obtain the position coordinates of the key elements of the football field, the football and the robot, thus significantly reducing the amount of information required for image processing. In addition to this, this paper builds Petri network models for different role robots to achieve different motion state control and analyses the temporal error of the robot's motion. The image processing approach and Petri net modelling used in this paper provide research directions for future indoor multi-robot localization approaches and task allocation.