Robust Automatic Parking without Odometry using an Evolutionary Fuzzy Logic Controller

Robust Automatic Parking without Odometry using an Evolutionary Fuzzy Logic Controller

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 the training data, using an evolutionary fuzzy system. Furthermore, it also finds the green zone for the ready-to-reverse position in which parking is possible just by reversing. It has been tested on a 4-wheeled Pioneer mobile robot which emulates the real vehicle.

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 the training data, using an evolutionary fuzzy system. Furthermore, it also finds the green zone for the ready-to-reverse position in which parking is possible just by reversing. It has been tested on a 4-wheeled Pioneer mobile robot which emulates the real vehicle.