Local logic optimization algorithm for autonomous mobile robot based on fuzzy logic

Abstract

In an unknown environment, autonomous mobile robots rely on sensors to continually obtain information about the surrounding environment, discern the location of obstacles, make calculations and make decisions independently. The existing navigation algorithms are prone to repetition on the rigid path in the face of complex environment such as U-shape, which leads to the navigation can not continue. To this end, this paper presents a local optimization navigation algorithm based on fuzzy logic, using "recognition - memory" strategy to process the sensor information. In the path planning to retain the location of the recent path and angle characteristics and other related resources, the formation of "memory." When the current planning path forms a dead zone and runs repeatedly, "identification" is formed and the path and navigation decision are re-planned to avoid obstacles colliding. The simulation experiments under Webots Pro and Matlab show that the mobile robot can effectively avoid and avoid the dead zone under the guidance of fuzzy rules and realize better autonomous navigation..