Distributed parameterized predictive control for multi-robot curve tracking

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dc.creatorGabriel V. Pacheco
dc.creatorLuciano Cunha de Araújo Pimenta
dc.creatorGuilherme Vianna Raffo
dc.date.accessioned2025-05-23T13:33:57Z
dc.date.accessioned2025-09-09T00:35:09Z
dc.date.available2025-05-23T13:33:57Z
dc.date.issued2020
dc.identifier.doihttps://doi.org/10.1016/j.ifacol.2020.12.1054
dc.identifier.urihttps://hdl.handle.net/1843/82477
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartof21st IFAC World Congress
dc.rightsAcesso Restrito
dc.subjectRobôs - Sistemas de controle
dc.subject.otherVector fields, distributed model predictive control, alternating direction method of multipliers, multi-robot systems, coordination
dc.titleDistributed parameterized predictive control for multi-robot curve tracking
dc.typeArtigo de evento
local.citation.epage6
local.citation.spage1
local.description.resumoThis work proposes a guidance strategy of multiple robots to converge and circulate a curve while avoiding collisions by using a distributed model predictive control. To build the model predictive control framework, systems guided by control laws with parameters are considered, which laws are embedded in the optimization problem. After that, the same problem is distributed using the Alternating Direction Method of Multipliers and nonlinear optimization. To solve the task of convergence and circulation of a closed path, a vector field based control law is embedded in the predictive control scheme. The control law results from the sum of two components, a convergence term and a circulation term, whereas each term has one proportional parameter associated. Numerical results present an application example, and the strategy effectiveness is discussed.
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.initialsUFMG
local.url.externahttps://www.sciencedirect.com/science/article/pii/S2405896320314245

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