Robust Automatic Parking without Odometry Using Enhanced Fuzzy Logic Controller

Abstract

This paper develops a novel automatic parking algorithm based on a fuzzy logic controller with the vehicle pose for the input and the steering rate for the output. It localizes the vehicle by using only external sensors -a vision sensor and ultrasonic sensors. Then it automatically learns an optimal fuzzy if-then rule set from training data. This is possible using a genetic fuzzy system which optimizes the parameters for the fuzzy logic controller. Furthermore, it also finds the green zone of the ready-to-reverse position where parking is possible just by reversing. It has been tested on a Pioneer mobile robot which emulates the real vehicle.