Abstract
The work describes parallel robot calibration procedure by evolutionary algorithm (EA). The algorithm uses nature-inspired features such as genetic information exchange, mutation, survival of the fittest, leap into the unknown and others. Special test function with two minimums peculiar to the calibration problem is used for the EA parameters assessment. The calibration procedure by EA is powerful instrument for improving of the parallel robot accuracy. They are more perspective and more reliable for the robot parameters identification in comparison with known gradient methods.
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Vischer P. Improving the accuracy of parallel robots. PhD-thesis No 1570, Ecole Polytechnique Federale de Lausanne. Switzerland. 1996.
Kirkpatrick S., Gerlatt C.D.Jr. and Vecchi M.P. Optimization by Simulated Annealing, Science, 220, 671–680, 1983.
Fogel D.B. Evolutionary Computation: Toward a New Philosophy of Machine Intelligence, IEEE Press, Piscataway, NJ.
First International Contest on Evolutionary Optimization. http:/iridia.ac.be/langerman/ICEO.html
Clavel R. Conception d'un robot parallele rapide a 4 degres de liberte, PhD-thesis No 925, Ecole Polytechnique Federale de Lausanne, Switzerland, 1991.
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© 1997 Springer-Verlag Berlin Heidelberg
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Kokcharov, I. (1997). Calibration of parallel robots by evolutionary algorithm. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020257
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DOI: https://doi.org/10.1007/BFb0020257
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