Decision-making system of soccer-playing robots using finite state machine based on skill hierarchy and path planning through Bezier polynomials

Abstract

The decision-making mechanism of robotic systems is a fundamental component for the robots’ autonomous control. Like soccer-playing robots, a system must be created such that the strategy is maximized to both chances of scoring and blocking, thus, obtaining a successful play. With the goal of expanding the range of practical applications for robotic systems and contributing to the progress of the design of mobile robots, this study designs a decision-making system using Finite State Machine (FSM) for the action-role selection and Bezier curvature algorithm for the path planning. The presented design follows the skill hierarchy – team strategy layer, role layer and action layer. The study limits the number of players per team to two soccer-playing robots. Each role has a different action to perform as strategized by FSM. The navigation of the robots is established by following a repeatedly modified Bezier curve. The results show that the system using FSM wins the game at 60% chance compared to a system without action planning. Moreover, the Bezier curvature algorithm is effective if both the robot is in the center area of the soccer field. However, the robot spins erroneously at locations near the edges of the soccer field.