Design of radial basis function-based controller for autonomous parking of wheeled vehicles

This work describes the development of an efficient automated parking support system for passenger cars. By using advances in artificial neural network technology and a classical combination of linear feedback and feedforward control, the authors propose a novel design for a parking motion controller. The paper presents the results of the controller design and analysis, including parking problem analysis, feedback controller stability analysis, formulation and optimal solution of the parking trajectory planning problem, and design of a novel parking motion planning architecture based on a radial basis function network. A general case of backward parking is emulated using the proposed controller. The emulation results reveal high efficiency of the presented approach and demonstrate that the proposed system can implemented on a typical passenger car.

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