SENSOR-BASED DRIVING OF A CAR WITH FUZZY INFERENCING VLSI CHIPS AND BOARDS
François G. Pin, Yutaka W. Watanabe · 1992
This paper discusses the sensor-based driving of a car in a-priori unknown environments using ``human-like`` reasoning schemes. The schemes are implemented on custom-designed VLSI fuzzy inferencing boards and are used to investigate two control modes for driving a car on the basis of very sparse and imprecise range data. In the first mode, the car navigates fully autonomously, while in the second mode, the system acts as a driver`s aid providing the driver with linguistic (fuzzy) commands to turn left or right and speed up, slow down, stop, or back up depending on the obstacles perceived by the sensors. Experiments with both modes of control are described in which the system uses only three acoustic range (sonar) sensor channels to perceive the environment. Sample results are presented which illustrate the feasibility of developing autonomous navigation systems and robust safety enhancing driver`s aid using the new fuzzy inferencing VLSI hardware and ``human-like`` reasoning schemes.