Volume-based Transition Zone Assessment of Hybrid Unmanned Aerial-Underwater Vehicles

Aoki, Vivian Misaki; Evald, Paulo Jefferson Dias de Oliveira; Pinheiro, Pedro M.; Silva, Cesar Bastos da; Cardoso, Dayana dos Santos; Cunha, Mauro André Barbosa; Drews, Paul

doi:10.1109/lars/sbr/wre56824.2022.9995961

Cited by 3 publications

(2 citation statements)

References 35 publications

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“…Furthermore, throughout the development of this work, studies were carried out in areas complementary to trajectory planning, such as vehicle design, modeling, control, simulation, visual-based navigation, and prototyping [Grando et al 2020, Horn et al 2020, Aoki et al 2021, Aoki et al 2022a, Aoki et al 2022b, Pedroso et al 2022] (all six of them published in LARS, QualisCC B1). Other publications also explore the use of deep reinforcement learning for mapless navigation and obstacle avoidance in aerial and underwater environments [Grando et al 2021, Grando et al 2022a, Grando et al 2022b] (one of them published in ICRA, QualisCC A1; and two of them published in LARS, QualisCC B1).…”

Section: Contributionsmentioning

confidence: 99%

Trajectory Planning of an Aerial-Underwater Hybrid Vehicle Based on Heuristics for Energy Efficiency

Pinheiro,

A. Neto,

Drews Jr.

2023

Anais Estendidos Do XV Simpósio Brasileiro De Robótica E XX Simpósio Latino-Americano De Robótica (SBR/LARS Estendido 2023)

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This 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.

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Section: Contributionsmentioning

confidence: 99%

Trajectory Planning of an Aerial-Underwater Hybrid Vehicle Based on Heuristics for Energy Efficiency

Pinheiro,

A. Neto,

Drews Jr.

2023

Anais Estendidos Do XV Simpósio Brasileiro De Robótica E XX Simpósio Latino-Americano De Robótica (SBR/LARS Estendido 2023)

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“…At present, the research of HAUV motion model and its characteristics is in the preliminary exploration stage. A team from Brazil studied the forces crossing the water surface and proposed a volumetric geometric environmental transition model [26] and a variable density function model [27]. A hydrodynamic model of a folding wing FHAUV crossing the water surface is established by a team from China, the motions of different angles, axial velocity, thrust and density is calculated [28] and a method for estimating underwater fluid forces is proposed with angular velocity and angle of attack [29].…”

Section: Introductionmentioning

confidence: 99%

Trajectory Tracking Control of Fixed-Wing Hybrid Aerial Underwater Vehicle Subject to Wind and Wave Disturbances

Li,

Jin,

et al. 2024

J Intell Robot Syst

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The hybrid aerial underwater vehicle (HAUV) could operate in the air and underwater might provide a great convenience for aerial and underwater exploration, and the fixed-wing HAUV (FHAUV) has time, space and cost advantages in future large-scale applications, while the large difference between the aerial and underwater environments is a challenge to control, especially in the air/water transition. However, for FHAUV control, there is a lack of research on phenomena or problems caused by large changes in the air/water transition. In addition, the effects of wind, wave, other factors and conditions on motion control are not investigated. This paper presents the first control study on the above issues. The motion model of FHAUV is developed, with the effects of wind and wave disturbances. Then, this paper improves a cascade gain scheduling (CGS) PID for different media environments (air and water) and proposes a cascade state feedback (CSF) control strategy to address the convergence problem of FHAUV control caused by large speed change in the air/water transition. In the comparisons of the two control schemes in various tracking cases including trajectory slopes, reference speeds, wind and wave disturbances, CSF has a better control effect, convergence rate and robustness; the key factors and conditions of the air/water transition are investigated, the critical relations and feasible domains of the trajectory slopes and reference speeds that the FHAUV must meet to successfully exit the water and enter the air are obtained, the critical slope decreases as the reference speed increases, and the feasible domain of CSF is larger than that of CGS, revealing that CSF is superior than CGS for exiting the water.

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Nonlinear and reinforcement learning control for motion of hybrid aerial underwater vehicle

Li,

Zhou,

et al. 2024

Neural Comput & Applic

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Volume-based Transition Zone Assessment of Hybrid Unmanned Aerial-Underwater Vehicles

Cited by 3 publications

References 35 publications

Trajectory Planning of an Aerial-Underwater Hybrid Vehicle Based on Heuristics for Energy Efficiency

Trajectory Planning of an Aerial-Underwater Hybrid Vehicle Based on Heuristics for Energy Efficiency

Trajectory Tracking Control of Fixed-Wing Hybrid Aerial Underwater Vehicle Subject to Wind and Wave Disturbances

Nonlinear and reinforcement learning control for motion of hybrid aerial underwater vehicle

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