Abstract
This article provides an overview of studies at the Oak Ridge National Laboratory (ORNL) of neural networks running on parallel machines applied to the problems of autonomous robotics. The first section provides the motivation for our work in autonomous robotics and introduces the computational hardware in use. Section 2 presents two theorems concerning the storage capacity and stability of neural networks. Section 3 presents a novel load-balancing algorithm implemented with a neural network. Section 4 introduces the robotics test bed now in place. Section 5 concerns navigation issues in the test-bed system. Finally, Section 6 presents a frequency-coded network model and shows how Darwinian techniques are applied to issues of parameter optimization and on-line design.
Research performed at Oak Ridge National Laboratory, operated by Martin Marietta Energy Systems, Inc., for the U.S. Department of Energy under Contract No. DE-AC05-84OR21400.
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Barhen, J., Dress, W.B., Jorgensen, C.C. (1989). Applications of Concurrent Neuromorphic Algorithms for Autonomous Robots. In: Eckmiller, R., v.d. Malsburg, C. (eds) Neural Computers. Springer Study Edition, vol 41. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-83740-1_34
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DOI: https://doi.org/10.1007/978-3-642-83740-1_34
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