Sugeno Fuzzy Logic Analysis: Navigation of Multiple Humanoids in Complex Environments

Abstract

This paper presents sugeno fuzzy system with hybridized membership functions for the determination of exact turning angles for the humanoid robots during their path traversal from starting point to goal point. This helps the robot to reach the destination effectively by avoiding the hurdles in the path and obtains the global minimal path. The hybridized membership functions used in the sugeno fuzzy approach plays a key role in providing the exact turning angles to avoid hurdles. Image sensors and ultrasonic sensors are used for mapping the environment and, also provide the hurdle distances to the fuzzy controller as input parameter. The hurdle distances from the robot in front, left and right direction are the input parameter to the fuzzy controller and exact turning angle is the output parameter from the controller. The developed controller is carried out in both simulation and experimental environment having complex hurdles. A comparison has been made between the results of both simulation and experimental scenariosand, a good agreement is found among those with minimal deviations.