Abstract
Sensor based robot control systems can overcome many of the difficulties which are caused by unknown or uncertain models of the environment. Conventional sensor based control systems require explicit knowledge of the kinematics and dynamics of the robot arm and a careful calibration of the sensor system. In-stead, adaptive neural controllers can be used to build an internal representation of the camera-motor correspondence from exemplar behaviour and adapt where necessary. In that case, static models are not necessary anymore, and the system can cope with changing behaviour of the robot (wear and tear, payload correction) and its sensors (changing lighting conditions, calibration and re-calibration).
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© 1995 Springer Science+Business Media New York
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Jansen, A., van der Smagt, P., Groen, F. (1995). Nested Networks for Robot Control. In: Murray, A.F. (eds) Applications of Neural Networks. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-2379-3_9
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DOI: https://doi.org/10.1007/978-1-4757-2379-3_9
Publisher Name: Springer, Boston, MA
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