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A new controller for the optimization of the movement of an exploration vehicle is proposed in this paper. Measurements of obstacle and goal's distance and direction are anticipated to be imprecise however, because the performance of ultrasonic sensors is degraded in complex environments. So a support vector machine is presented that can determine a trajectory for an exploration vehicle through unknown environments, even in the presence of imprecise sensor data. The controller that is proposed includes a support vector machine and a fuzzy logic controller. According to the target position, the support vector machine to determine the optimal angle and velocity required for the exploration vehicle to reach the goal. The fuzzy logic controller is designed to determine the velocity of the left and right wheels of the exploration vehicle. Thus generated, the velocity was optimized according to the measures obtained by the support vector machine. Finally, based on the optimal velocity of vehicle, the output membership function was modified. The method fully utilizes the potential of the SVM and fuzzy logic to determine vehicle navigation. And the genetic algorithm is used to confirm best parameters of SVM. The simulation results illustrate the robustness of a support vector machine approach regard to sensor imperfections, and could find the optimal path. The proposed controller allowed the exploration vehicle to reach the goal quickly and effectively.