ICANN ’93 pp 293-296 | Cite as

A real-time Robot demonstration controlled by the BSP400 Neurocomputer

  • Jan N. H. Heemskerk
  • Patrick T. W. Hudson
Conference paper


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.


Neural Network Sensor Node Learning Rule Light Sensor Modular Neural Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London Limited 1993

Authors and Affiliations

  • Jan N. H. Heemskerk
    • 1
  • Patrick T. W. Hudson
    • 1
  1. 1.Unit of Experimental and Theoretical PsychologyLeiden UniversityLeidenThe Netherlands

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