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Neural Network Based Low Cost Autonomous Vehicle

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Abstract

Abstract-The conceptual high-level design of a low cost neural network (NN) based autonomous vehicle is presented. Focus is on the domain of indoor as well as small outdoor applications such as mail delivery system among neighboring organizations. The design is based on four independent neural networks attached with ultrasonic rangefinders; Inertial Measuring Unit (IMU) and GPS receiver. The NN model is the multilayer feed-forward network with back-propagation training algorithm. The NN implementation is done using the Atmel RISC microcontrollers (MC). The absolute referencing is achieved with the combination of GPS receiver and IMU. A vector map is incorporated for road following and path planning. The arbitration scheme is based on fuzzy logic and implemented with the same series of MC. The low cost components make the design feasible for our daily use applications

Topics: Neural Network, autonomous vehicle backpropagation, ultrasonic
Year: 2009
OAI identifier: oai:CiteSeerX.psu:10.1.1.135.661
Provided by: CiteSeerX
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