Ge
Shi
,
Azadeh
Shariati
,
Ian
Eames
and
Helge
Wurdemann
*
Department of Mechanical Engineering, University College London, London, UK. E-mail: h.wurdemann@ucl.ac.uk
First published on 9th November 2022
A purely mechanical-driven haptic feedback system was developed for amputees by [G. Shi et al., IEEE Trans. Haptics, 2020, 13, 204–210]. The fingertip ellipsoid modulates the compression force and transmits it to the feedback actuator when the finger interacts with an object. In this paper, the haptic feedback system has been modelled using finite deformation theory. For the ellipsoid fingertip, the compression behaviour between two rigid, flat surfaces has been studied and can predict the force-indentation trend and deformed shape of the membrane with the contact area. For the feedback actuator, the model for the flat membrane is developed with elastic theory, in which the deformation resulting in contact area increase has been studied. The model has been validated with experimental results, which consists of the fingertip ellipsoid membrane being compressed by a rigid surface and the feedback actuator being pressurised. The results of force-indentation, pressure-indentation and the deformation of the membrane from ellipsoid modelling lay within the experimental data and fit the non-linear trend well. The results from modelling the feedback actuator have the same trend as the experimental data in the force–pressure relationship. The haptic feedback system is consistent as a functional tactile sensor after validation. We present the modelling and validation of the proposed model for the mechanical driven haptic feedback system.
Although research from ref. 1 and 2 provide reviews of mechano, vibro, electrotactile and hybrid systems, purely mechanical-driven feedback approaches, however, are seldom investigated. In 1933, Rosset described how pressure at the prosthetic fingertip could be transmitted to amputees.3 In 1953, Conzelman et al. were granted a patent on a similar haptic feedback system with incompressible fluid.4 In ref. 5, this initial idea resulted in a pneumatic closed-loop haptic feedback system prototype, which used compressible air instead of incompressible fluid, and was validated by subjects. Technical challenges of the two aforementioned approaches include the liability (i.e., appearance of leakages) and fabrication process. Pneumatic transmission has further limitations due to its density and compressibility when displacement of only a few millilitres in volume is required. In ref. 6, hydraulic haptic feedback system with conductive fluid and electronics to actuate was introduced and validated. The related PCBs and battery squeezed into upper-limb prosthetic give the amputees extra weight to carry. In ref. 7, we presented the development and evaluation of a 3D printed mechano-tactile haptic feedback system using a soft hydraulic tactile fingertip sensor. This haptic feedback system is purely mechanical and relies on a coupled hydraulic system. The latest technology in multi-material additive manufacturing, such as the Stratasys Objet500 Connex3, allows printing of dual material such as VeroClear, a polymethyl methacrylate, and Agilus 30, a thermoplastic elastomer with flexible, rubber-like qualities. Our haptic feedback system is made of an Agilus 30 fingertip sensor integrated with a VeroClear finger linked to a wearable haptic mechano-tactile actuator with an Agilus 30 membrane. The sensor and actuator are 3D printed and can be easily integrated into (3D printed) body-powered upper-limb prostheses. In the case of distal amputations, such as transradial amputees, the haptic feedback actuator can be interfaced with the residual limb/forearm through a socket. The range of forces that can be transmitted using our haptic feedback interface relies on the dimension of the design of the fingertip and haptic feedback actuator as well as the used material.
In this paper, we propose an analytical modelling approach for a fluidic haptic feedback system by understanding the deformation of the ellipsoid soft membrane (resulting in fluidic pressure change) and then the transmission of pressure to the haptic feedback membrane resulting in tactile forces. On the other hand, our analytical model will be able to provide the basis for future optimisation problems for the design for sensing interfaces based on ellipsoid membranes, for instance. In this sense, the design of membranes could be optimised by considering a defined force range as input and understanding, what material and geometric dimensions a sensor should be made of.
Despite the application of our proposed model to the fluidic haptic feedback system in this paper, there are a number of soft robotic areas that might benefit from our mathematical formulation. In general, our approach might support kinematic modelling of robotic structures that are made of a number of soft elastic membranes. Input such as the dimension of the membrane, material properties and membrane thickness will then return the overall deformation and compression of each. In particular, examples might include the locomotion of a bio-inspired robot made of a series of silicone elastomer spheres that are deformed by shape memory allow coils8 or a robotic manipulator made of stackable Hyperelastic Ballooning Membranes.9 Our analytical model would be able to determine the deformed shape of the membranes under certain forces and, hence, the motion of the actuators. Other examples concern the creation of tactile sensing elements that are pre-shaped ellipsoid membranes.10–13 Here, our mathematical model would be suitable to establish a calibration curve between the compression and the force acting on the membranes. For instance, the BioTac SP tactile sensor by Syntouch is made of an ellipsoid membrane which is filled with incompressible fluid inside the cavity able to measure mechano- and vibro-tactile forces through the pressure change. With our proposed analytical model, any deformation would return an increase in hydrostatic pressure and result in a force response. Beyond the application in the field of soft material robotics, ellipsoid membranes further exist in biological cells (fat cells and liver hepatocytes), tumours and organs (glands), which our analytical model could be applied to.14–16 Examples include studies on mechanical properties of capsules and biological cells with ellipsoid shapes.17–19 Applying our analytical model could help to diagnose unhealthy soft tissue and distinguish cancerous from healthy tissue during palpation and compression procedures.20
The problem of inflation and compression with different geometries rather than flat membrane inflation have been investigated in detail. For instance, Feng et al. studied the inflation of an axisymmetric semi-spherical elastic membrane that compressed with a flat rigid plate with a rigid support underneath.27 This model has been widely applied and its feasibility validated through applications such as micro-capsule and cell wall modelling,18,19,28,29 safety airbag modelling,30 modelling the behaviour of the membrane in contact with curved surfaces.31 Inflation and compression of toroidal membranes, in which the geometry has positive and negative curvatures, have also been studied.32,33 In addition, the inflation and compression of an elliptical membrane as a fingertip pulp model has been modelled by Serina.34 However, the mismatch of the angle in the parametric equation and polar coordinator causes the model to be less accurate.
In addition to the continuous elastic deformation theory, other methods have been applied to model the fingertip, such as Finite Element Analysis (FEA) and the static elastic model. In ref. 35, fingertip pulp was modelled as a solid elastic semi-sphere composed of an infinite number of vertical springs. In ref. 36 and 37, the compression of a fingertip was modelled by FEA methods and the force response fits the results of the model in ref. 34.
Fingertip modelling in the existing literature either requires tremendous computation like FEA or assumes the fingertip behaves as an elastic chunk and cannot predict the shape of deformation. As a result, the analytical method for calculating the compression of an ellipsoid fingertip membrane is still undeveloped. Hence, the contribution of our paper lies in a new analytical model for an ellipsoid geometry membrane allowing us to understand the change in shape, volume and, hence, pressure during deformation. We distinguish the non-linearity caused both by the ellipsoid shape and hyperelasity of materials. The results of our proposed model have been used to model and experimentally validate the response of the feedback actuator in order to predict the performance of a haptic feedback system with different material, different dimensions.
• The ellipsoid membrane is axisymmetric in both undeformed and deformed conditions, and the shear stresses are zero from the profile view.
• The thickness of the ellipsoid membrane h0 is small relative to the entire dimensions, and therefore the change of thickness during deformation is considered negligible.
• The volume of the ellipsoid membrane is constant during compression due to the fluid being relatively incompressible.
• The pressure under the contact region is evenly distributed and equal to the pressure inside.
The fingertip is assumed as an ellipsoid membrane that is compressed vertically and quasi-statically by a flat, rigid, smooth plate from the top as shown in Fig. 1. The membrane is modelled as an axisymmetric, ellipsoid membrane with rigid fixed support underneath and filled with incompressible, inviscid fluid. The membrane is fitted into the cylindrical coordinates (x,y,θ) to describe the shape in its undeformed state. The centroid of the ellipsoid membrane is located at the origin with a major principal axis length a0 on the x axis and the minor principal axis length b0 on the y axis. The second cylindrical coordinates (ρ,η,θ) are used for compressed ellipsoid membranes. The xΓ denotes the value of x corresponding to the boundary Γ between the contact and free inflation regions. Elastic materials that can be fitted by a hyperelastic model, e.g., the Mooney–Rivlin model, Yeoh, or neo-Hookean model, are compatible with our model. In general, compatible materials would need to satisfy a number of criteria such as: it can be assumed that the material is incompressible, capable of large deformations and able to return to its initial state.
W = C1(I1 − 3) + C2(I2 − 3), | (1) |
(2) |
(3) |
The principal stretch ratio λ1 is in meridian direction subscripts 1 and λ2 is in circumferential direction with subscripts 2, defined as the ratio between the undeformed lengths of an infinitesimal arc element and the deformed lengths, are:
(4) |
(5) |
(6) |
(7) |
(8) |
(9) |
(10) |
(11) |
η′ = 0, (x < xΓ). | (12) |
Therefore, the principal stretch in the contact region is
(13) |
(14) |
Fc = AcPc = πxΓ2Pc, | (15) |
(16) |
(17) |
(18) |
(19) |
• Inflation: the membrane is first inflated with pressure P0 to the desired dimension with initial conditions λ1 = λ2 = λi = ω at the pole of the ellipsoid membrane (x = 0). The bisection method is applied to find the initial values λi that satisfy the condition ω = 0 at x = a0 and record λ2(inflation). This condition shows that the membrane is still an ellipse shape with a perpendicular tangent at x = a0. Once the dimension and shape of the ellipsoid membrane are determined, the volume of the inflated membrane Vinf is calculated using eqn (11).
• Compression: the second step requires assuming a liquid pressure Pc and contact point xΓ for the compressed ellipsoid. According to the initial condition λ1 = λ2 = λ0, apply the bisection method to find the λ0 that satisfies the second boundary conditions as shown in Fig. 2, which is the λ2(inflation) = λ2(contact) at x = a0. The volume of the compressed ellipsoid Vcom is then calculated by eqn (17) to check if the volume is equal to the inflated volume Vinf. If it is not equal, re-assume a contact boundary xΓ then repeat the previous calculation until the results satisfy all the restrictions and conditions shown in eqn (19).
Both steps are solved using the Runge Kutta method in Matlab 2021 with a tolerance of 10−2%; the solution is usually obtained in less than 20 iterations.
(20) |
(21) |
Fig. 5 Comparison between the model results and the experimental data. (a) Reaction force Fc on the membrane versus indentation H0. Reaction force Fc from the model was calculated by eqn (21) (b) hydrostatic pressure Pcversus indentation H0. Hydrostatic pressure Pc in the model was assumed during the calculation of eqn (9) to meet boundary conditions. (c) Contact area Acversus reaction force Fc on the membrane. Contact area Ac from the model is calculated by Ac = πxΓ2. |
The contact area is a flat surface on top of the membrane that reflects the configuration of deformation in the compression stage. The contact area Ac calculated using Fc and Pc, i.e. (Ac = Fc/Pc). Fig. 5(c) shows that Ac increases rapidly at the initial compression stage, with 60% of the total contact area achieved at 4–5 N.
Fig. 6(a) shows the shape change of the membrane in the inflation stage based on the results from the model. At the initial inflation stage, the height rapidly increases, which in turn increases the aspect ratio (τ = b0/a0) as shown in Fig. 6(a). After the initial shape change, the entire membrane expands evenly by applying a higher pressure level with a larger initial stretch ratio λ0. Fig. 6(b) and (c) illustrate the stress resultant Ti and the stretch ratio λiversus the horizontal position x. Inflation leads to nonuniform distribution of stress and strain. The maximum stress resultant T1 and stretch ratio λ1 in the circumferential direction occurs at the pole of the ellipsoid membrane (x = 0) and decreases towards the edge of the membrane (x = a0). The stress resultant and the stretch ratio in the meridian direction demonstrate an opposite behaviour compared to the circumferential direction. The transition from initial inflation to entire expansion depends on the material property and aspect ratio. In order to inflate the ellipsoid membrane from a0 = 4.5 mm,τ = 0.6 to ρ = 9 mm with τ = 0.78. In this instance, it happens at λ0 = 2.3 and Pi = 2.1 kPa with Agilus30. The inflation determines the lower bound of pressure in compression.
Fig. 6 Inflated membrane. At the initial inflation stage, the height increases rapidly, causing the aspect ratio τ to likewise increases. With higher pressure inflation, the entire membrane inflates evenly. (a) Cross-section view of the inflated membranes with different initial stretch ratios λ0 calculated by eqn (10). (b) Principle stretch ratios λ1 and λ2 of an ellipsoid membrane calculated by eqn (9). (c) Resultant stress in the circumferential and meridian directions calculated by eqn (7). |
Under compression, the membrane is flattened on the top by a rigid plate while the free inflation region bulges around the membrane to keep the inside volume constant as shown in Fig. 7(a). Further compression results in higher hydrostatic pressure. Meanwhile, the stress resultant and the stretch ratio in the meridian and circumferential direction increase at all levels in response.
Fig. 7 Compressed membrane. With higher indentation, the membrane is flattened on the top and inflated on the side. (a) Profiles of compressed membranes with different indentation and pressure. The position of the membrane is calculated by eqn (16). (b) Principle stretch ratios λ1 and λ2 of an ellipsoid membrane calculated by eqn (14). (c) Resultant stress in the circumferential and meridian direction calculated by eqn (7). |
The points encircled with red in Fig. 7(b) and (c) are the contact boundary Γ, where Γ = xΓ/a0. From x = 0 to x = xΓ, the stretch ratio (λ1,λ2) and the stress resultant (T1,T2) remains similar to their initial values but briefly decrease. In the free inflation region (xΓ < x < a0), the stretch ratio and the stress resultant change their behaviour by increasing in the meridian direction and decreasing in the circumferential direction. In this instance, the edge of the ellipsoid membrane is constrained by satisfying λ2(inflation) = λ2(compressed) = 2 at (x = a0).
After verifying the analytical model of an ellipse compression, the valve is open and forms a closed cavity with the ellipsoid membrane and feedback actuator. Increased hydrostatic pressure can transmit to the ∅9 mm membrane of the feedback actuator and pressurise the membrane to generate the blocked force. The hydrostatic pressure Pc and force from the feedback actuator Ff show a linear relationship in the experimental data and model results (Fig. 8). Overall, the model results show a higher force response than the experimental data; the model result reach a maximum force of 1.98 N at pressure 17.9 kPa while feedback force in the experimental data is 1.68 N at same pressure.
Fig. 8 Linear relationships between the output force (calculated by eqn (21)) at the feedback actuator and the hydrostatic pressure for each feedback actuator membrane. |
After the membrane is inflated to the desired shape, the volume and the edge of the membrane is constrained by converging λ2(inflation) = λ2(contact) at x = a0 as it can be seen in Fig. 7(a) and (b). Within the contact region x ∈ (0,xΓ), the stretch of the membrane is isotropic, i.e. ‖λ1 − λ2‖ < 10−2. As the membrane is compressed further and the contact region increases, the zone of isotropic stretching likewise increases. Where x ∈ (xΓ,a0), the stretch in the meridian and circumferential directions are anisotropic. Meridian stress on the symmetry plane constrains the indention depth of the membrane. Moreover, circumferential stress constrains the expansion of the membrane in the vertical view.
As the indentation depth H0 increases close to max, the initial stretch ratio λ0 gradually increases. The stress resultant Ti likewise increases with each compression step as it is evident from (Fig. 7(b) and (c)). The membrane resists further compression by acting with higher stiffness of the material on all membranes with a higher stretch ratio and stress. The maximum indentation depth max is determined by the inflated height Ĥinf and original height b0, which means the inflation stage provides the lower bound of the indentation.
During the inflation stage, slight pressure might lead to a significant expansion in the geometry due to lack of constraints at the edge of the membrane for the initial inflation. The initial dimension of the ellipsoid membrane a0 and b0 with the inflation condition P0 and λ0 are varied and have different combinations of values but can yield the same desired dimension. As a0 and b0 decrease with increasing inflation pressure P0, Ĥinf increases as well as the maximum indentation depth max evident by a good agreement with the experiment data in Fig. 5 at higher inflation pressure values P0. Hence, the combination with a slightly larger inflation height Ĥinf at higher inflation pressure P0 has been selected and compared with the indentation depth max. The initial inflation produces a nonuniform stretch and stress on the membrane as shown in Fig. 6(b) and (c). As the inflation pressure increases, the deviation level of stress and stretch ratio in the meridian and circumferential direction increases. Hence, the ellipsoid membrane shows anisotropy in the inflated states.
It is worth noting that we established a number of assumptions for our analytical model. In particular, the assumptions, that the model considers the compression of a pre-inflated membrane and that the thickness of the membrane remains unchanged, might add errors to our modelling formulation. In our paper, the membrane of the fingertip shows an anisotropic behaviour in its inflated state. In the experiments, however, the membrane is unstretched. When the inflated membrane is compressed in the computational model, the offset of the stress caused by the initial inflation remains. Hence, the results might show higher stress levels compared to the experimental results. On the other side, the change of thickness during the deformation is neglected because the thickness of the membrane is significantly smaller than the width and height of the fingertip membrane. A limitation might occur if membranes are considered that have larger thicknesses.
During the experimental procedure, the feedback actuator is mounted on a socket. The deflated membrane is then in full contact with the load cell restricting free inflation and generating blocked forces. The membrane exhibits a change in volume. Volume change ΔV (Fig. 3) can be calculated by ΔV = dfΔh. Under 17.935 kPa, the volume change ΔV is 1.38 mm3, which means the total volume change of the flat membrane being pressurised by Pc is 0.432% of the volume of the inflated membrane Vinf. Hence, the volume change of the ellipsoid membrane, in which the fluid flows to the feedback actuator, is negligible.
The maximum deviation between the experimental and computational results for the feedback actuator is about 18.56% at a pressure value of 17.9 kPa in Fig. 8. It can be observed that the deviation proportionally increases with the hydrostatic pressure. The reasons for this discrepancy might be manifold. One reason might be due to the increase in friction between the surface of the elastic membrane and the load cell preventing the membrane to stretch. This behaviour is neglected in our computational model of the feedback actuator. Another reason might relate to the manufacturing process of the actuator. The membrane is fixed onto the solid structure by the multi-material 3D printer by Stratasys. The bond between these two materials might vary in strength.
The computational results of our analytical model are compared to results reported in the literature as summarised in Table 1. The table shows the calculated or measured reaction force Fc at H0 = 0.5 mm and 2 mm indentation. As a reference, the experimental results of force-indentation of a fingertip were reported by Serina.39 Then, the computational results of an FEA36 are listed in the table as well as the results of our model using the material constants of skin tissue (C1 = 13400 Pa, C2 = 29500 Pa)34 on the one hand and the material contestants of Aglius30 on the other hand. Maximum errors are calculated with respect to the experimental results of a fingertip compression. When considering the constants of Aglius30 material, the maximum error is similar to the results of the FEA. The error is lower (14.7%) for results taking the material constants of human skin tissue as input.
0.5 mm | 2 mm | ε max | |
---|---|---|---|
a ε max: maximum deviation error compared with experimental results from the fingertip compression. | |||
Exp. results of fingertip compression39 | 0.32 N | 1.94 N | — |
FEA results36 | 0.36 N | 2.09 N | 19.3%(0.5 mm) |
Analytical (Skin) | 0.27 N | 1.99 N | 14.7%(0.5 mm) |
Analytical (Agilus30) | 0.38 N | 2.11 N | 18.7%(0.5 mm) |
Our theoretical computations can predict the inflated and compressed states of the ellipsoid membrane. Hence, by designing the haptic feedback system for different sizes of fingertip membranes and feedback actuators with different elastic materials, the model can predict the performance of the haptic feedback system and optimise the design to replicate the force-indentation curve. The deformation theory for the ellipsoid membrane is not only limited to modelling the fingertip compression but also has the potential to model inflation and compression of an ellipsoid membrane in generic cases.
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