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Optimal velocity planning based on the solution of the Euler-Lagrange equations with a neural network based velocity regression

Article dans une revue avec comité de lecture
Author
ccGHNATIOS, Chady
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
ccDI LORENZO, Daniele
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
564849 ESI Group [ESI Group]
CHAMPANEY, Victor
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
ccCUETO, Elias
161327 Aragón Institute of Engineering Research [Zaragoza] [I3A]
ccCHINESTA SORIA, Francisco
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
1166977 CNRS@CREATE Ltd.

URI
http://hdl.handle.net/10985/25773
DOI
10.3934/dcdss.2023080
Date
2024-07
Journal
Discrete and Continuous Dynamical Systems - Series S (DCDS-S)

Abstract

Trajectory optimization is a complex process that includes an infinite number of possibilities and combinations. This work focuses on a particular aspect of the trajectory optimization, related to the optimization of a velocity along a predefined path, with the aim of minimizing power consumption. To tackle the problem, a functional formulation and minimization strategy is developed, by means of the Euler-Lagrange equation. The minimization is later performed using a neural network approach. The strategy is deemed Lagrange-Net, as it is based on the minimization of the energy functional, by the means of Lagrange's equation and neural network approximations.

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OPTIMAL VELOCITY PLANNING BASED ...
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