In this chapter, a system for displaying the softness of different materials was pro-
mechanical properties of various materials were characterized by conducting mechan-
ical compression tests. These data were used by the processing software to actuate
the display. A Proportional-Integral-Derivative (PID) controller was designed and
optimized to control the shaft of the actuator to produce the same sensation of soft-
ness measured by the force sensor. Different materials were simulated by the tactile
display and compared to the real objects. Experiments were conducted on the tac-
tile display using human subjects and the results were recorded and presented. The
results showed that the developed tactile display can replicate the softness of mate-
rials very closely and has great potential for identifying and categorizing objects by
touch. In summation, it has proved to be a feasible technique with great potential use
in robotic surgery, training facilities, virtual reality and minimally invasive surgery
Chapter 6
Conclusion and Future Work
6.1
Conclusions
In this thesis, a novel inverse model program of estimating hyperelastic and hyper-
viscoelastic material parameters has been developed based on the FE model and
experiment of indentation using spherical indenters. MultiStart global optimization
with single and multi-objective function methods, based on the Nelder-Mead simplex
algorithm, have been employed for solving these inverse problems. Parameters of a
suitable hyperelastic model have been identified for two different closed cell foams,
namely EVA and B1. The validity of assuming frictionless contact between the in-
denter and foams during these indentation tests, as well as zero Poisson’s ratio for
closed cell foams, have been demonstrated using the same inverse model problem.
The effect of indentation depth and indenter size were also investigated in estimated
flexibility of this inverse method makes it suitable for general identification processes
where direct measurements are not easily applicable. Applicability of this method is
demonstrated on problem of hyper-viscoelastic material parameters identification for
bovine liver tissue. It has, however, been shown that the accuracy of parameter iden-
tification using inverse indentation modeling is sensitive to both indentation depth
and indenter size. It has also been shown that, by increasing the indentation depth,
the difference between identified parameters using different indenter sizes decreases
correspondingly.
Two methods of real time parameter identification were proposed for nonlinear
soft materials. The proposed methods were based on variance calculation and pa-
rameter estimation using the Kalman filter algorithm. Both the methods were based
on inverse FE modeling of spherical indentation test. The FE model of indentation
was pre-evaluated in feasible range of material parameters and used as a reference
data source for both the methods. Results are illustrated and compared in terms of
precision and computing time. It was found that the variance calculation method
required much less computation time compared to the Kalman filter method, which
makes it suitable for real time identification procedures at high indentation rates.
Although the Kalman filter method showed less scattering in identified parameters,
it was prone to failure and, in some cases, was unable to achieve good convergence
characteristics in contrast to the variance method. The proposed bounding methods
for the Kalman filter estimation were implemented and their results compared. It
certain estimation processes such as if the estimate is selected on the state space
boundary. However, during the normal identification processes, the Projection and
Penalty methods yielded better results compared to the Nearest Neighbor method.
The performance of both algorithms were assessed in material parameter identifica-
tion and was found to yield a performance success rate of greater than 90% based
on experiments in which random indentations (150 indentations per experiment) and
three different indentation rates were employed. It was also found that increasing
the indentation rate leads to more accurate and repeatable results, which perhaps is
due to the reduced time dependent behavior of the studied materials. Identification
results, from both the variance and Kalman filter methods, were found to be com-
parable. However the way these methods work leads to discrete estimate space for
the variance method and continuous space for the Kalman filter method with less
scattering.
A novel magneto-rheological fluid (MRF) based tactile display is proposed and its
magnetic FE model is constructed and validated by Gauss meter measurements. An
accurate finite element (FE) model of human finger pad is constructed and validated in
experiments of finger pad contact with soft and relatively rigid materials. Hyperfoam
material parameters of the identified elastomers from the Chapter 2 are used for
validation of the finger pad model. FE models of the human finger pad and the
proposed tactile display are used in a model based control scenario for the proposed
display. FE models of the elastomers developed in Chapter 2 are used for calculation
proposed display. Experiments are performed on biological tissue and soft nonlinear
foams. The results of experiments represented in this work show that the proposed
control model and the display design are suitable for tactile applications such as
displaying softness. Future work, such as recreation of softness for stiffer materials,
will necessitate the use of stronger electromagnetic and amplifier circuits.
A novel system for displaying the softness of nonlinear materials was proposed and
tested based on linear actuator. The main components consisted of a linear actuator,
a force sensor, and processing software for each of which a detailed description was
provided. Contact of human finger pad with the proposed display is modeled and
deformation in finger pad is considered for controlling the actuator.The mechanical
properties of various materials were characterized by conducting mechanical compres-
sion tests. These data were used by the processing software to actuate the display.
A Proportional-Integral-Derivative (PID) controller was designed and optimized to
control the shaft of the actuator to produce the same sensation of softness measured
by the force sensor. Different materials were simulated by the tactile display and com-
pared to the real objects. Experiments were conducted on the tactile display using
human subjects and the results were recorded and presented. The results showed that
the developed tactile display can replicate the softness of materials very closely and
has great potential for identifying and categorizing objects by touch. In summation,
it has proved to be a feasible technique with great potential use in robotic surgery,