A Path Planning Algorithm for a Dynamic Environment Based on Proper Generalized Decomposition
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Title
A Path Planning Algorithm for a Dynamic Environment Based on Proper Generalized DecompositionAuthor (s)
Date
2020-12-19Publisher
MDPIISSN
2227-7390Bibliographic citation
Falcó, Antonio; Hilario, Lucía; Montés, Nicolás; Mora, Marta C.; Nadal, Enrique. 2020. "A Path Planning Algorithm for a Dynamic Environment Based on Proper Generalized Decomposition" Mathematics 8, no. 12: 2245. https://doi.org/10.3390/math8122245Type
info:eu-repo/semantics/articlePublisher version
https://www.mdpi.com/2227-7390/8/12/2245Version
info:eu-repo/semantics/publishedVersionSubject
Abstract
A necessity in the design of a path planning algorithm is to account for the environment.
If the movement of the mobile robot is through a dynamic environment, the algorithm needs to
include the main constraint: ... [+]
A necessity in the design of a path planning algorithm is to account for the environment.
If the movement of the mobile robot is through a dynamic environment, the algorithm needs to
include the main constraint: real-time collision avoidance. This kind of problem has been studied
by different researchers suggesting different techniques to solve the problem of how to design a
trajectory of a mobile robot avoiding collisions with dynamic obstacles. One of these algorithms is the
artificial potential field (APF), proposed by O. Khatib in 1986, where a set of an artificial potential field
is generated to attract the mobile robot to the goal and to repel the obstacles. This is one of the best
options to obtain the trajectory of a mobile robot in real-time (RT). However, the main disadvantage
is the presence of deadlocks. The mobile robot can be trapped in one of the local minima. In 1988,
J.F. Canny suggested an alternative solution using harmonic functions satisfying the Laplace partial
differential equation. When this article appeared, it was nearly impossible to apply this algorithm
to RT applications. Years later a novel technique called proper generalized decomposition (PGD)
appeared to solve partial differential equations, including parameters, the main appeal being that the
solution is obtained once in life, including all the possible parameters. Our previous work, published
in 2018, was the first approach to study the possibility of applying the PGD to designing a path
planning alternative to the algorithms that nowadays exist. The target of this work is to improve our
first approach while including dynamic obstacles as extra parameters. [-]
Is part of
Mathematics, vol. 8, n.12 (2020)Funder Name
Generalitat Valenciana | Ministerio de Ciencia, Innovación y Universidades
Project code
GVA/2019/124 | RTI2018-093521-B-C32
Rights
(c) 2020 by the authors
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
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