Hydrodynamic Performance Enhancement of Unmanned Underwater Gliders with Soft Robotic Morphing Wings for Agility Improvement

A. Giordano; G. De Meurichy; V. Telazzi; C. Mucignat; I. Lunati; D. A. L. M. Louchard; M. Iovieno; S. F. Armanini

cs.ROFeb 23, 2026

Hydrodynamic Performance Enhancement of Unmanned Underwater Gliders with Soft Robotic Morphing Wings for Agility Improvement

Authors: A. Giordano, G. De Meurichy, V. Telazzi, C. Mucignat, I. Lunati, D. A. L. M. Louchard, M. Iovieno, S. F. Armanini,

Organizations: Laboratory of Sustainability Robotics, Empa, 8600 Dübendorf, Switzerland. · Department of Aeronautics, Imperial College London, SW7 2AZ London, United Kingdom. · Laboratory for Computational Engineering, Empa, 8600 Dübendorf, Switzerland. · Dipartimento di Ingegneria Meccanica e Aerospaziale (DIMEAS), Politecnico di Torino, 10129 Torino, Italy. ·

Abstract

This work assesses the hydrodynamic efficiency of Underwater Unmanned Vehicles (UUVs) equipped with soft morphing wings compared to conventional rigid wings. Unlike rigid wings, deformable counterparts can alter their aerodynamic properties on demand. Improvements in hydrodynamic efficiency extend a UUV's operational range and may determine mission feasibility. Structural and Computational Fluid Dynamics (CFD) simulations were conducted for both a soft morphing wing and a UUV incorporating it. The results show that a UUV employing soft wings achieves 9.75 percent higher overall efficiency than an equivalent vehicle with traditional rigid wings. These findings confirm the potential of soft robotics to enhance underwater vehicle performance, particularly in applications requiring pressure-agnostic operation.

Figures & tables

Fig. 1: Cross-sectional view of the soft morphing wing showing its profile and internal structure for all deformation levels tested in [ Giordano2024 ] . From top to bottom:

0\text{\,}\mathrm{ml}

30\text{\,}\mathrm{ml}

60\text{\,}\mathrm{ml}

90\text{\,}\mathrm{ml}

, and

120\text{\,}\mathrm{ml}

. All profiles shown are the results of the simulations performed for the present work.

Property	Aluminium	Ecoflex 00-50	PLA
Density [kg m -3 ]	$2.70\text{\times}{10}^{3}$	$1.07\text{\times}{10}^{3}$	$1250$
Young’s Mod. [MPa]	$6.90\text{\times}{10}^{4}$	–	$3.50\text{\times}{10}^{3}$
Poisson’s Ratio	$3.30\text{\times}{10}^{-1}$	–	$2.00\text{\times}{10}^{-1}$
Bulk Mod. [MPa]	$6.96\text{\times}{10}^{4}$	–	$1.94\text{\times}{10}^{3}$
Shear Mod. [MPa]	$2.60\text{\times}{10}^{4}$	–	$1.46\text{\times}{10}^{3}$
$C_{10}$ [MPa]	–	$4.76\text{\times}{10}^{-2}$	–

TABLE I: Material Properties of Aluminium, Ecoflex 00-50, and PLA

Fig. 2: Correlation between the inflation levels of the soft wing [ Giordano2024 ] and the isotropic pressure field applied in the simulations to reproduce equivalent deformations. A second-order polynomial fit

P(I)=-0.025I^{2}+0.7273I-0.1543

was applied to the four experimental data points, enabling the extrapolation of 3 additional inflation levels (yellow).

Fig. 3: Camber profiles of the soft wing from the experiments performed in [ Giordano2024 ] , Fig. 5 (solid black lines), and corresponding profiles as an output of the structural simulations performed for the present work (coloured dots).

Inflation	RMS Error	Max Error	Pressure
[ mL]	[mm]	[mm]	[kPa]
0	0.921	1.60	0.00
30	0.835	1.26	18.8
60	0.632	1.05	35.5
90	0.301	0.543	44.3
120	1.07	1.60	51.2

TABLE II: Comparison between inflation, input pressure, root mean square (RMS) and maximum (max) error.

Fig. 4: Hydrodynamic characterisation of the soft wing at

Re_{2}\simeq

9.20\text{\times}{10}^{4}

(free-stream velocity $U_{2}=$0.40\text{\,}\mathrm{m}\text{/}\mathrm{s}

). Solid lines represent the water tunnel measurements, as reported in [ Giordano2024 ] , while the dotted lines correspond to the force values obtained from the CFD simulations performed for the present work.

Fig. 5: Domain of all CFD simulation performed by the authors and involving an underwater glider. The cylinder represents the UUV and has a total length of $\overline{IJ}=L_{UUV}$ . The parallelepiped of vertices A, B, C, D, E, F, G, and H delimits the water volume. $L_{a}=L_{b}=L_{h}=1.5\cdot L_{UUV}$ , $L_{f}=5\cdot L_{UUV}$ .

Fig. 6: Two views of the 3D rendering of the simulated Underwater Unmanned Vehicle (UUV) implementing the soft wing.

Fig. 7: CFD validation of the simulations using the Underwater Unmanned Vehicle (UUV) presented in [ singh2017cfd ] and [ ichihashi2008development ] .

Fig. 8: Left hand side : simulation of pitching moments

q

for each inflation tested experimentally at a flow-speed of

0.26\text{\,}\mathrm{m}\text{\,}{\mathrm{s}}^{-1}

. Right hand side : simulation of rolling moments

p

for all tested inflations at

\alpha=0\degree

. Each inflation shown in this plot is given under the assumption that the two wings are inflated in opposite directions (

30

and

-30

mL,

60

and

-60

mL,

90

and

-90

mL, and

120

and

-120

mL).

Fig. 9: Hydrodynamic characterization of the selected Underwater Unmanned Vehicle (UUV) implementing the soft wing at all inflations tested in [ Giordano2024 ] and the interpolated

15\text{\,}\mathrm{ml}

. Free-flow speed

U_{1}=

0.26\text{,}\mathrm{m}\text{/}\mathrm{s}$$ .

Underwater Robotics

Underwater robotics develops autonomous and remotely operated machines for navigation, inspection, manipulation, and exploration in aquatic environments.

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Jul 15, 2026J/K move · Enter open · S save

Design, Modeling and Experimental Validation of a Miniature Hybrid Underwater Glider With Large-Range Foldable Deflectable Wings

Yongjian Zhu, Yusen Tao, Feitian Zhang

Robotics and Control Laboratory, School of Advanced Manufacturing and Robotics, and the State Key Laboratory of Turbulence and Complex Systems, Peking University, Beijing 100871, China

Robot Dynamics Identification Underwater Robotics

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Miniature hybrid underwater gliders have attracted increasing attention for long-endurance ocean observation and confined-space inspection. Large-range wing reconfiguration offers a promising yet largely unexplored approach for simultaneously enhancing maneuverability and shape adaptability in constrained underwater environments. However, such morphing introduces substantial challenges in mechanical integration, dynamic modeling, and hydrodynamic characterization. This paper presents FoDeGlider, a miniature hybrid underwater glider equipped with two independently actuated wings capable of large-range folding and deflection. To capture configuration-dependent variations in mass distribution, center-of-geometry location, and hydrodynamic loading, a multibody dynamics model is developed by treating wing configuration as a structural variable. A composite rigid body algorithm (CRBA)-based projection formulates the composite inertia, wrench transformations, and component-level hydrodynamics into a unified Fossen-form dynamic model applicable to arbitrary wing configurations. A sequential parameter-identification framework is further proposed to estimate fuselage and wing hydrodynamic coefficients, resulting in an open benchmark dataset for model identification and validation. Extensive experiments are conducted, the results of which demonstrate accurate dynamic modeling and parameter identification across diverse morphing configurations. Gate traversal experiments further validate FoDeGlider's ability to actively reconfigure its morphology during locomotion, enabling enhanced navigation in confined underwater environments.

Abstract

Underwater Robotics

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