Autonomous parallel parking of four wheeled vehicles utilizing adoptive Fuzzy-Neuro control system

The study presents an autonomous sensor based parallel parking maneuver on a car-like mobile robot. This project focuses on parallel parking the car-like mobile robot within a given scenario following the fifth degree polynomial reference path in a backward maneuver. Training data, gathered from the fifth degree polynomial path, is subjected to subtractive clustering algorithm to determine the fuzzy controller and trained by the adaptive neurofuzzy inference system. The project uses eight ultrasonic sensors, placed strategically to avoid radial imprecision, to detect the obstacles along its path; an accelerometer is also used to detect the inclination of the car-like mobile robot (CLMR). The sensors acquire necessary sensor data for the Neuro-Fuzzy Inference System to determine the proper motion direction at each sampling point. The efficiency of the proposed Neuro-Fuzzy Controller (NFC) design is revealed through the actual results.