Integrated fuzzy global path following and obstacle avoidance for mobile robots

Motion planning is the process of computing a path, i.e., a sequence of robot configurations, allowing it to move from one place to another. It is a central problem in the development of autonomous mobile robots. This is true indeed, but when the environment of the robot becomes complex, i.e., uncertain, partially known, with moving obstacles or other robots, it takes much more than global motion planning to achieve motion autonomy. In this case, the ability to detect unexpected events and react accordingly becomes essential. Reactivity provides the robot with an important mechanism to immediate respond to unpredicted environmental changes. This paper describes an intelligent path planning system for omnidirectional mobile robots. Our proposed solution to the dual need for global path planning and reactivity is to adopt a two-level model: at the upper level, a planner provides the system with a global path, based on the available knowledge; at the lower level, a reactive controller follows this given global path, while dealing with the environmental contingencies. The control architecture, presented in this paper, relies upon two main complementary modules: a global path planner, that computes a nominal path between the current configuration of the robot and its goal, and a reactive local planner, whose purpose is to generate the appropriate commands for the actuators of the robot, so as to follow the global path as close as possible, while reacting in realtime to unexpected events by locally adapting the robots movements, so as to avoid collisions with unpredicted or moving obstacles. This reactive local planner consists of two separate fuzzy controllers for path following and obstacle avoidance. The functioning of the proposed system with respect to omnidirectional mobile robots and results of simulated experiments will be presented.