Scalable Optimal Motion Planning for Multi-Agent Systems by Cosserat Theory of Rods

Fuente: arXiv
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Auteurs principaux: Golestaneh, Amirreza Fahim, Hammond, Maxwell, Cichella, Venanzio
Format: Preprint
Publié: 2024
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author Golestaneh, Amirreza Fahim
Hammond, Maxwell
Cichella, Venanzio
author_facet Golestaneh, Amirreza Fahim
Hammond, Maxwell
Cichella, Venanzio
contents We address the motion planning problem for large multi-agent systems, utilizing Cosserat rod theory to model the dynamic behavior of vehicle formations. The problem is formulated as an optimal control problem over partial differential equations (PDEs) that describe the system as a continuum. This approach ensures scalability with respect to the number of vehicles, as the problem's complexity remains unaffected by the size of the formation. The numerical discretization of the governing equations and problem's constraints is achieved through Bernstein surface polynomials, facilitating the conversion of the optimal control problem into a nonlinear programming (NLP) problem. This NLP problem is subsequently solved using off-the-shelf optimization software. We present several properties and algorithms related to Bernstein surface polynomials to support the selection of this methodology. Numerical demonstrations underscore the efficacy of this mathematical framework.
format Preprint
id arxiv_https___arxiv_org_abs_2406_07684
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Scalable Optimal Motion Planning for Multi-Agent Systems by Cosserat Theory of Rods
Golestaneh, Amirreza Fahim
Hammond, Maxwell
Cichella, Venanzio
Optimization and Control
Numerical Analysis
Dynamical Systems
We address the motion planning problem for large multi-agent systems, utilizing Cosserat rod theory to model the dynamic behavior of vehicle formations. The problem is formulated as an optimal control problem over partial differential equations (PDEs) that describe the system as a continuum. This approach ensures scalability with respect to the number of vehicles, as the problem's complexity remains unaffected by the size of the formation. The numerical discretization of the governing equations and problem's constraints is achieved through Bernstein surface polynomials, facilitating the conversion of the optimal control problem into a nonlinear programming (NLP) problem. This NLP problem is subsequently solved using off-the-shelf optimization software. We present several properties and algorithms related to Bernstein surface polynomials to support the selection of this methodology. Numerical demonstrations underscore the efficacy of this mathematical framework.
title Scalable Optimal Motion Planning for Multi-Agent Systems by Cosserat Theory of Rods
topic Optimization and Control
Numerical Analysis
Dynamical Systems
url https://arxiv.org/abs/2406.07684