Minimal exposure paths in time-varying fields: a semi-lagrangian approach

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dc.creatorArmando Alves Neto
dc.creatorVíctor Costa da Silva Campos
dc.creatorDouglas G. Macharet
dc.date.accessioned2025-05-27T14:28:34Z
dc.date.accessioned2025-09-09T00:57:54Z
dc.date.available2025-05-27T14:28:34Z
dc.date.issued2023
dc.identifier.doi10.1109/lra.2022.3230595
dc.identifier.issn23773766
dc.identifier.urihttps://hdl.handle.net/1843/82521
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofIEEE Robotics and Automation Letters
dc.rightsAcesso Restrito
dc.subjectRobôs - Sistemas de controle
dc.subject.otherSensors , Wireless sensor networks , Robot sensing systems , Trajectory , Sensor phenomena and characterization , Cost function , Computational modeling
dc.subject.otherSensor networks , motion and path planning , optimization and optimal control
dc.subject.otherMinimal Exposure , Minimum Path , Time-varying Field , Exposure Paths , semi-Lagrangian Approach , Optimal Path , Wireless Sensor Networks , Sensor Model , Field Sensor , Lowest Exposure , Static Ones , Navigation , Optimization Problem , Value Function , Running Time , Optimal Control , Control Input , Control Problem , Intensity Function , Path Planning , Papers In The Literature , Heterogeneous Network , Line System , Square Grid , Delaunay Triangulation , Voronoi Diagram , Mapping Algorithm , Distinct Intervals , Optimal Control Problem , Total Exposure
dc.titleMinimal exposure paths in time-varying fields: a semi-lagrangian approach
dc.typeArtigo de periódico
local.citation.epage671
local.citation.issue2
local.citation.spage664
local.citation.volume8
local.description.resumoIn the context of Wireless Sensor Networks (WSNs), the Minimal Exposure Path (MEP) represents an important metric to evaluate the quality of network services. Most of the current literature is concentrated on stationary sensors, while few works have addressed the existence of moving nodes. Mobile Wireless Sensor Networks (MWSNs) present a great potential for detecting invaders compared to static ones, but dealing with dynamic sensors significantly increases the coverage complexity since the overall exposure of the sensor field depends on time. Therefore, in this letter, we propose an approach to compute Minimal Exposure Paths in time-varying fields based on a control optimization method called semi-Lagrangian (SL) scheme, in such a way that an intruder will be able to penetrate the dynamic field with the lowest exposure. The SL has already been proven to reach the optimal Minimal Exposure Path (MEP) on static WSNs, but concerning dynamic nodes, the proof is much more complicated. Then, we propose a heuristics that provides convergence of the SL algorithm to a result we conjecture to be the optimal one. Results with different time-varying sensor models in obstacle-free and cluttered environments have been presented and discussed.
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.departmentICX - DEPARTAMENTO DE CIÊNCIA DA COMPUTAÇÃO
local.publisher.initialsUFMG
local.url.externahttps://ieeexplore.ieee.org/document/9992088

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