BEHAVIORS FUSION FOR A MOBILE ROBOT USING FUZZY BEHAVIORS WEIGHTS TUNED BY REAL CODED GENETIC ALGORITHM

Volume: 
Volume 12
Abstract 

Coordination between different behaviors, such as goal reaching, obstacle avoidance, reaching the collision–free space, and wall following, all of these represent a big problem in navigation of the mobile robots in unknown or partially known environments. In this paper a solution of this problem is presented using switched gains, these gains are inferred from a fuzzy fusion system (FFS). These gains are weighted and tuned by a real coded Genetic Algorithm (RCGA) based on a fitness function that ensures a safe and short path to the object. The proposed technique assures a safe and efficient navigation.

Author 
K. N. Faris M. T. El-Hagry