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Scalable time-constrained planning of multi-robot systems

This paper presents a scalable procedure for time-constrained planning of a class of uncertain nonlinear multi-robot systems. In particular, we consider N robotic agents operating in a workspace which contains regions of interest (RoI), in which atomic propositions for each robot are assigned. The m...

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Autores principales: Nikou, Alexandros, Heshmati-alamdari, Shahab, Dimarogonas, Dimos V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7548002/
https://www.ncbi.nlm.nih.gov/pubmed/33088023
http://dx.doi.org/10.1007/s10514-020-09937-6
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author Nikou, Alexandros
Heshmati-alamdari, Shahab
Dimarogonas, Dimos V.
author_facet Nikou, Alexandros
Heshmati-alamdari, Shahab
Dimarogonas, Dimos V.
author_sort Nikou, Alexandros
collection PubMed
description This paper presents a scalable procedure for time-constrained planning of a class of uncertain nonlinear multi-robot systems. In particular, we consider N robotic agents operating in a workspace which contains regions of interest (RoI), in which atomic propositions for each robot are assigned. The main goal is to design decentralized and robust control laws so that each robot meets an individual high-level specification given as a metric interval temporal logic (MITL), while using only local information based on a limited sensing radius. Furthermore, the robots need to fulfill certain desired transient constraints such as collision avoidance between them. The controllers, which guarantee the transition between regions, consist of two terms: a nominal control input, which is computed online and is the solution of a decentralized finite-horizon optimal control problem (DFHOCP); and an additive state feedback law which is computed offline and guarantees that the real trajectories of the system will belong to a hyper-tube centered along the nominal trajectory. The controllers serve as actions for the individual weighted transition system (WTS) of each robot, and the time duration required for the transition between regions is modeled by a weight. The DFHOCP is solved at every sampling time by each robot and then necessary information is exchanged between neighboring robots. The proposed approach is scalable since it does not require a product computation among the WTS of the robots. The proposed framework is experimentally tested and the results show that the proposed framework is promising for solving real-life robotic as well as industrial applications.
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spelling pubmed-75480022020-10-19 Scalable time-constrained planning of multi-robot systems Nikou, Alexandros Heshmati-alamdari, Shahab Dimarogonas, Dimos V. Auton Robots Article This paper presents a scalable procedure for time-constrained planning of a class of uncertain nonlinear multi-robot systems. In particular, we consider N robotic agents operating in a workspace which contains regions of interest (RoI), in which atomic propositions for each robot are assigned. The main goal is to design decentralized and robust control laws so that each robot meets an individual high-level specification given as a metric interval temporal logic (MITL), while using only local information based on a limited sensing radius. Furthermore, the robots need to fulfill certain desired transient constraints such as collision avoidance between them. The controllers, which guarantee the transition between regions, consist of two terms: a nominal control input, which is computed online and is the solution of a decentralized finite-horizon optimal control problem (DFHOCP); and an additive state feedback law which is computed offline and guarantees that the real trajectories of the system will belong to a hyper-tube centered along the nominal trajectory. The controllers serve as actions for the individual weighted transition system (WTS) of each robot, and the time duration required for the transition between regions is modeled by a weight. The DFHOCP is solved at every sampling time by each robot and then necessary information is exchanged between neighboring robots. The proposed approach is scalable since it does not require a product computation among the WTS of the robots. The proposed framework is experimentally tested and the results show that the proposed framework is promising for solving real-life robotic as well as industrial applications. Springer US 2020-07-31 2020 /pmc/articles/PMC7548002/ /pubmed/33088023 http://dx.doi.org/10.1007/s10514-020-09937-6 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Nikou, Alexandros
Heshmati-alamdari, Shahab
Dimarogonas, Dimos V.
Scalable time-constrained planning of multi-robot systems
title Scalable time-constrained planning of multi-robot systems
title_full Scalable time-constrained planning of multi-robot systems
title_fullStr Scalable time-constrained planning of multi-robot systems
title_full_unstemmed Scalable time-constrained planning of multi-robot systems
title_short Scalable time-constrained planning of multi-robot systems
title_sort scalable time-constrained planning of multi-robot systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7548002/
https://www.ncbi.nlm.nih.gov/pubmed/33088023
http://dx.doi.org/10.1007/s10514-020-09937-6
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