A controller is developed to guide a four-wheeled vehicle through an unknown environment. The vehicle is equipped with an ultrasonic sensor that can rotate to survey the neighboring environment. A new path planning algorithm is developed that reduces the computational time while avoiding obstacles. The vehicle uses a fuzzy-logic controller to determine the corresponding change in steering. While fuzzy-logic controllers exhibit robustness under varying operating conditions, it is difficult to design a good controller when observations about the system are scarce or when the system has large number of inputs and outputs. Due to this fact, the performance of the fuzzy-logic controller is improved using nonlinear programming techniques. The algorithm automatically generates the fuzzy rules and redefines the shape of the membership sets of input and output variables for an optimal performance of the controller. The effects of changing: the velocity of the vehicle, the range of the ultrasonic sensor, and the time step of the controller of the autonomous vehicle are discussed
