2-Dimensional SVFC Application in Path Planning of Mobile Robots

A 2-dimensional single variable fuzzy controller (SVFC) is introduced to achieve the path planning for mobile robots. With fusing some fuzzy and uncertain information obtained from distance and angle sensors, and invoking the corresponding fuzzy logic inference, this SVFC can output the action instruction, which then determines the behavior control, realizing the optimal non-collision path planning for the mobile robots. The essential jobs in this whole design process consist of the defining the fuzzy sets, discrete grades and membership functions for the input and output parameters, establishing the rules for fuzzy controller, and evaluating the fuzzy control response. Due to the complex computation of the high dimension matrixes achieved from the SVFC, an off-line inquiring table scheme is proposed to gain the inference response, which strictly follows the Mamdani inference rules, viz. Max-Min integrated theory, a practical fuzzy control response table is presented in sequence. Moreover, after constituting the working environmental model, the numerical simulation is implemented to estimate the performance of this fuzzy control system. The simulation result shows that the SVFC leads to the intelligent, simple, and accurate path guidance for mobile robots, indicating the behavior control and realizing the navigation tasks.