Optimal trajectory planning combining model-based and data-driven hybrid approaches

Chady Ghnatios; Daniele Di Lorenzo; Victor Champaney; Amine Ammar; Elias Cueto; Francisco Chinesta

doi:10.1186/s40323-024-00266-2

Optimal trajectory planning combining model-based and data-driven hybrid approaches

Chady Ghnatios, Daniele Di Lorenzo, Victor Champaney, Amine Ammar, Elias Cueto, Francisco Chinesta

Research output: Contribution to journal › Article › peer-review

Original language	English
Article number	10
Journal	Advanced Modeling and Simulation in Engineering Sciences
Volume	11
Issue number	1
DOIs	https://doi.org/10.1186/s40323-024-00266-2
State	Published - Dec 2024
Externally published	Yes

ASJC Scopus Subject Areas

Modeling and Simulation
Engineering (miscellaneous)
Computer Science Applications
Applied Mathematics

Keywords

Artificial intelligence
Euler–Lagrange equations
Machine learning
Optimal planning
Physics informed machine learning
Trajectory optimization

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10.1186/s40323-024-00266-2

Cite this

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title = "Optimal trajectory planning combining model-based and data-driven hybrid approaches",

keywords = "Artificial intelligence, Euler–Lagrange equations, Machine learning, Optimal planning, Physics informed machine learning, Trajectory optimization",

author = "Chady Ghnatios and \{Di Lorenzo\}, Daniele and Victor Champaney and Amine Ammar and Elias Cueto and Francisco Chinesta",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2024.",

year = "2024",

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doi = "10.1186/s40323-024-00266-2",

language = "English",

volume = "11",

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T1 - Optimal trajectory planning combining model-based and data-driven hybrid approaches

AU - Ghnatios, Chady

AU - Di Lorenzo, Daniele

AU - Champaney, Victor

AU - Ammar, Amine

AU - Cueto, Elias

AU - Chinesta, Francisco

N1 - Publisher Copyright: © The Author(s) 2024.

PY - 2024/12

Y1 - 2024/12

KW - Artificial intelligence

KW - Euler–Lagrange equations

KW - Machine learning

KW - Optimal planning

KW - Physics informed machine learning

KW - Trajectory optimization

UR - https://www.scopus.com/pages/publications/85191879272

UR - https://www.scopus.com/inward/citedby.url?scp=85191879272&partnerID=8YFLogxK

U2 - 10.1186/s40323-024-00266-2

DO - 10.1186/s40323-024-00266-2

M3 - Article

AN - SCOPUS:85191879272

VL - 11

JO - Advanced Modeling and Simulation in Engineering Sciences

JF - Advanced Modeling and Simulation in Engineering Sciences

IS - 1

M1 - 10

ER -

Optimal trajectory planning combining model-based and data-driven hybrid approaches

ASJC Scopus Subject Areas

Keywords

Access to Document

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