Mobile robot wall-following control using a fuzzy cerebellar model articulation controller with group-based strategy bacterial foraging optimization

Mobile robot wall-following control using a fuzzy cerebellar model articulation controller with group-based strategy bacterial foraging optimization

Blog Article

In this study, a fuzzy cerebellar model articulation controller based on group-based strategy bacterial foraging optimization is proposed for mobile robot wall-following control.In fuzzy cerebellar model articulation controller, the inputs are the distance between the sonar and the wall, and the outputs are the angular velocity of two wheels.The proposed group-based strategy bacterial foraging Denture Creams optimization learning algorithm is used to adjust the parameters of fuzzy cerebellar model articulation controller model.The proposed group-based strategy bacterial foraging optimization has the advantages of global search, evolutionary strategies, and group evolution to speed up the convergent rate.

A new fitness function is defined to evaluate the performance Dish Caddies of mobile robot wall-following control.The fitness function includes four assessment factors which are defined as follows: (1) maintaining safe distance between the mobile robot and the wall, (2) ensuring successfully running a cycle, (3) avoiding mobile robot collisions, and (4) mobile robot running at a maximum speed.The experimental results show that the proposed group-based strategy bacterial foraging optimization obtains a better wall-following control than other methods in unknown environments.