Motion planning for mobile robots using a fuzzy layered goal-oriented approach

In this paper, a layered goal-oriented motion planning strategy using fuzzy logic is developed for a mobile robot navigating in an unknown environment. Information about the global goal and long-range sensory data are used by the first layer of the planner to produce an intermediate goal, referred to as the way-point, that gives an optimal direction in terms of seeking the goal within the detected area. The second layer of the planner takes this way-point as a sub-goal and, using short-range sensory data, guides the robot to reach the sub-goal while avoiding collisions. In this approach, there is no assumption about the environment. Due to its simplicity and capability for real-time implementation, fuzzy logic has been used for the proposed motion planning strategy. The resulting navigation system is implemented on a real mobile robot, Koala, and tested in various environments. Experimental results are presented which demonstrate the effectiveness of the proposed fuzzy navigation system.