Robust automatic parallel parking in tight spaces via fuzzy logic

This paper develops and experimentally demonstrates a robust automatic parallel parking algorithm for parking in tight spaces. Novel fuzzy logic controllers are designed for each step of the maneuvering process. The controllers are first demonstrated by simulation using the kinematic model of a skid steering autonomous ground vehicle (AGV). They are then demonstrated experimentally on a skid steering AGV and it is shown that the developed algorithm has the ability to parallel park AGVs in tight spaces under both vehicle localization errors and parking space detection errors. This paper also presents a genetic fuzzy system which uses a genetic algorithm's learning ability to determine effective parameters for the developed fuzzy logic controllers. The genetic fuzzy system is used to tune the fuzzy logic algorithm for both a skid steering AGV and a front-wheel steering AGV.