Por favor, use este identificador para citar o enlazar este ítem: https://repositorio.cetys.mx/handle/60000/452
Título : Studies in computational intelligence
Título de capítulo: Acceleration of path planning computation based on evolutionary artificial potential field for non-static environments
Autor : Orozco Rosas, Ulises
Picos, Kenia
Montiel, Oscar
Otros Autores: CETYS Universidad
Palabras clave : Path planning;Evolutionary artificial potential field;Mobile robots;Graphics processing unit;Heterogeneous computing
Sede: Sistemas
Fecha de publicación : 28-feb-2020
Resumen : In this work, a mobile robot path-planning algorithm based on the evolutionary artificial potential field (EAPF) for non-static environments is presented. With the aim to accelerate the path planning computation, the EAPF algorithm is implemented employing novel parallel computing architectures. The EAPF algorithm is capable of deriving optimal potential field functions using evolutionary computation to generate accurate and efficient paths to drive a mobile robot from the start point to the goal point without colliding with obstacles in static and non-static environments. The algorithm allows parallel implementation to accelerate the computation to obtain better results in a reasonable runtime. Comparative performance analysis in terms of path length and computation time is provided. The experiments were specifically designed to show the effectiveness and the efficiency of the mobile robot path-planning algorithm based on the EAPF in a sequential implementation on CPU, a parallel implementation on CPU, and a parallel implementation on GPU.
URI : DOI: 10.1007/978-3-030-35445-9_22
ISSN : 1860-949X
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