Trajectory planning of an aerial-underwater hybrid vehicle based on heuristics for energy efficiency

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dc.creatorPedro M. Pinheiro
dc.creatorArmando Alves Neto
dc.creatorPaulo Lilles Jorge Drews Junior
dc.date.accessioned2025-05-30T14:12:31Z
dc.date.accessioned2025-09-09T00:02:41Z
dc.date.available2025-05-30T14:12:31Z
dc.date.issued2023
dc.identifier.doihttps://doi.org/10.5753/sbrlars_estendido.2023.234779
dc.identifier.urihttps://hdl.handle.net/1843/82657
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofXV Simpósio Brasileiro de Robótica e XX Simpósio Latino-Americano de Robótica
dc.rightsAcesso Aberto
dc.subjectAeronave não tripulada
dc.subject.otherExploring ground effect in a hybrid aerial-aquatic unmanned vehicle
dc.subject.otherAnalysis of a hybrid unmanned aerial underwater vehicle considering the environment transition
dc.subject.otherSampling-based algorithms for optimal motion planning using closed-loop prediction
dc.subject.otherAttitude and altitude control of unmanned aerial-underwater vehicle based on incremental nonlinear dynamic inversion
dc.titleTrajectory planning of an aerial-underwater hybrid vehicle based on heuristics for energy efficiency
dc.typeArtigo de evento
local.description.resumoThis work studies the trajectory planning of an unmanned hybrid aerial-underwater vehicle (HUAUV) called Hydrone, which is being developed by the Intelligent Robotics and Automation Group (NAUTEC) of the Federal University of Rio Grande (FURG). This study presents a new trajectory planning algorithm, based on closed-loop rapidly exploring random trees (CL-RRT). This algorithm is developed for an HUAUV and introduces two heuristics to improve its energy efficiency in hybrid tasks. Simulated experiments were carried out in 135 virtual scenarios, comparing three approaches: one without heuristics and two with the proposed heuristics. Simulated results demonstrate that using the heuristics can significantly reduce energy consumption and even improve the vehicle’s average speed during missions. In particular, in 95% of the scenarios, the lowest energy consumption was achieved by one of the two heuristic-based algorithms. This article concludes by summarizing the findings and identifying potential future research opportunities.
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.initialsUFMG
local.url.externahttps://sol.sbc.org.br/index.php/sbrlars_estendido/article/view/27012

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