Abstract
We present research work in progress into the use of adaptive genetic algorithms (AGAs) to search for collision-free paths in an artificial potential field (APF) representation of a cluttered robotic work-cell. We argue that the AGA approach promises to avoid the drawback of other APF approaches which are vulnerable to entrapment by local minima.
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© 1995 Springer-Verlag/Wien
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Rylatt, R.M., Czarnecki, C.A., Routen, T.W. (1995). Adaptive Genetic Algorithms for Multi-Point Path Finding in Artificial Potential Fields. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7535-4_35
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DOI: https://doi.org/10.1007/978-3-7091-7535-4_35
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82692-8
Online ISBN: 978-3-7091-7535-4
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