Tao Huang, Ping Yang, Kaiming Yang, and Yu Zhu
Mobile robot, navigation, obstacle avoidance, T–S neuro-fuzzysystem
In this paper, a T–S neuro-fuzzy system is applied to a multi-sensor mobile robot. A fuzzy logic system is designed to complete the obstacle-avoiding and navigation, while a learning algorithm using neural network techniques is developed to tune the parameters of the membership functions and the weights of the neural network, and optimization of the whole system performance. Application of the proposed method, the mobile robot based on multi-sensor information fusion can adequately sense the environment around, autonomously avoid obstacles and trace the static or moving target, under the unknown environment generate reasonable trajectory to reach the target. The effectiveness and the efficiency of the proposed method are demonstrated by simulation studies and experimental validation.
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