Abstract
The “intelligence” of robots is not yet sufficient to deal with complex situations in many potential applications, for example in the service area or for industrial assembly. For this reason, engineers are looking for solutions which are based on biology rather than on classical technical approaches, as animals have shown that they can cope successfully with complex problems. Using neural networks is one step in this direction and has become quite fashionable. However, not each possible application of a neural net is technically useful. Three different areas will be presented where the use of neural networks has advantages over classical methods. This classification will be substantiated by practical experience from ETH projects on the gripping of unknown objects, on a vision system for a robot playing ping pong, and on localizing addresses on postal parcels.
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Schweitzer, G., Wen, J. (2000). Where Neural Nets Make Sense in Robotics. In: Cruse, H., Dean, J., Ritter, H. (eds) Prerational Intelligence: Adaptive Behavior and Intelligent Systems Without Symbols and Logic, Volume 1, Volume 2 Prerational Intelligence: Interdisciplinary Perspectives on the Behavior of Natural and Artificial Systems, Volume 3. Studies in Cognitive Systems, vol 26. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0870-9_34
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DOI: https://doi.org/10.1007/978-94-010-0870-9_34
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