VISUAL GUIDANCE OF AUTONOMOUS VEHICLE BASED ON FUZZY PERCEPTION

The paper describes a fuzzy perception based guidance of an autonomous ground vehicle. The technique proposed uses a visual servoing approach in which the control incorporates directly the visual feedback. The application involves guiding the vehicle through roadways by detecting the road edges from the image space. The vehicle and the scene models are established from the system behavior and the visually perceived features. The method is based on the fuzzy perception of the road edges from the gradient orientation image. In our work, the problem of road edge detection is viewed as a phenomena of perceiving gradient direction levels and then tracing the locus of the vectors which correspond to dominant linear features. In order to reinforce the detection process, the edge perception operator is formulated as a membership function applied on the gradient orientation image in the intensity domain. With this fusion process, the conventional number of edge levels are found to be reduced to minimum since the edge information obtained from the gradient direction image is complementary in the perception domain. The results obtained show the feasibility of the approach and the performances of the algorithm in a simulation of a real outdoor vehicle.