Machine Learning: Self-parking CarNEUROPA: A parallel system to self-park an autonomous mobile robot

using machine learning, published: Autonomous Mobile Systems, pages 182-192, Springer, ISBN: 3-540-60657-2

Authors: Matt Oberdorfer, Andreas Zell, Paul Levi http://dl.acm.org/citation.cfm?id=733691

SUMMARYWe introduce the architecture and system for an autonomous, mobile robot that navigates unsupervised in unknown lab environment guided by ultrasound and camera to find and park into market parking stalls. The machine learning features of the proposed system are 1) the simultaneous application of neural networks and symbol-processing components within an architecture with four levels of abstraction, 2) the use of a retina-like structure of receptive fields of neurons to guide focus and magnification of virtual eye, 3) the use of relatively small landmarks that are color-based detected, focused and then detected by a neural network, 4) the use of a rule-based system and a fuzzy controller to search for suitable parking spaces marked in the exploration phase.