Abstract
An actual implementation of a real-time, neural network controlled, robot car is presented in this paper. The simple car consists of two motors and 4 light sensors. Supervised learning behaviour of the car is achieved by using a neural network with adaptive connections. The car can be taught to avoid obstacles. The controlling neural network is implemented on the BSP400 neurocomputer, a Brain Style Processor with 400 nodes. A subset of the digital nodes in the BSP400 are connected by fixed weights to form logical circuits in order to re-train the car. In this way cooperative computation of both ’logical’ and ’neural’ processes are integrated into one system.
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© 1993 Springer-Verlag London Limited
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Heemskerk, J.N.H., Hudson, P.T.W. (1993). A real-time Robot demonstration controlled by the BSP400 Neurocomputer. In: Gielen, S., Kappen, B. (eds) ICANN ’93. ICANN 1993. Springer, London. https://doi.org/10.1007/978-1-4471-2063-6_67
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DOI: https://doi.org/10.1007/978-1-4471-2063-6_67
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