ACA-based Fuzzy Controller Design for Robot Soccer
This paper presents the use of an ant colony algorithm combined with a fuzzy logic controller (ACA-FLC) to optimize the movement of a soccer robot. Through ACA-FLC processes, the optimal angle and velocity of a moving robot in the work space were determined. At later stages of the study, more effective movement was obtained from ACA-FLC processes. The experimental scenarios involved a simulated 5-vs-5 soccer game and a MATLAB simulation, in which the proposed system dynamically directed the robot to the target position. The simulation results show that the ACA-FLC was able to choose a better position under any conditions it encountered. The ACA-based method is proposed to determine appropriate membership functions automatically for the fuzzy system so that the controlled robot can effectively move to any desired position in a 2-D space. Following the steps outlined above, the proposed ACA-FLC helped the robot reach the target quickly and effectively.
robot soccer ant colony algorithm fuzzy logic controller mobile robot