Path Plan of Robot Based on Neural-Fuzzy Control System

According to the issue of dynamic path plan of mobile robot in unknown environments from start to the destination with obstacle avoidance, a systemic neural-fuzzy control algorithm is proposed. Fuzzy logic control system is designed to do the input fuzzification, fuzzy reasoning rule base, output defuzzification. The simplified structure of neural network handling the fuzzy control is also designed. Train the network using QPSO. Solve the "dead cycle" problem in U-shaped obstacle through the storage and management strategy of status variable of robot. Experimental results show that under the control of the proposed systemic algorithm, mobile robot can moving toward the target, avoiding all kinds of obstacles, dynamically planning reasonable path, not getting into the dead cycle.