Acceleration of Path Planning
Computation Based on Evolutionary
Artificial Potential Field for Non-static
Environments
Ulises Orozco-Rosas, Kenia Picos and Oscar Montiel
Abstract In this work, a mobile robot path-planning algorithm based on the evolu-
tionary artificial potential field (EAPF) for non-static environments is presented. With
the aim to accelerate the path planning computation, the EAPF algorithm is imple-
mented 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 environ-
ments. 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.
Keywords Path planning · Evolutionary artificial potential field · Mobile robots ·
Graphics processing unit · Heterogeneous computing
U. Orozco-Rosas · K. Picos
CETYS Universidad, Centro de Innovación y Diseño (CEID), Av. CETYS Universidad No. 4, El
Lago, 22210 Tijuana, Baja California, Mexico
e-mail: ulises.orozco@cetys.mx
K. Picos
e-mail: kenia.picos@cetys.mx
O. Montiel (B )
Instituto Politécnico Nacional, CITEDI-IPN, Av. Instituto Politécnico Nacional No. 1310, Nueva
Tijuana, 22435 Tijuana, Baja California, Mexico
e-mail: oross@ipn.mx
© Springer Nature Switzerland AG 2020
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