A 13 x 13 square millimetre tri-axial taxel is presented which is suitable for some medical applications, for instance in assistive robotics that involves contact with humans or in prosthetics. Finite Element Analysis is carried out to determine what structure is the best to obtain a uniform distribution of pressure on the sensing areas underneath the structure. This structure has been fabricated in plastic with a 3D printer and a commercial tactile sensor has been used to implement the sensing areas. A three axis linear motorized translation stage with a tri-axial precision force sensor is used to find the parameters of the linear regression model and characterize the proposed taxel. The results are analysed to see to what extent the goal has been reached in this specific implementation.
Tactile sensors are basically arrays of force sensors. Most of these force sensors are made of polymers or conductive
rubbers to lower the cost, especially in the case of large area low-medium resolution tactile sensors. The price to pay for
such decrease in the cost and complexity is a worse performance. Hysteresis and drift are the two main sources of error.
This paper presents a method to reduce the error caused by hysteresis. This method is based on the generalized Prandtl-
Ishlinskii model that has been applied to characterize hysteresis and saturation nonlinearities in smart actuators. The
classical Prandtl-Ishlinskii model is not suitable because the lack of symmetry the output curves from the sensor show.
Other alternatives like the Preisach model are too complex to implement, especially taking into account that a tactile
sensor provides many data to process. The approximation error depends on several parameters as well as on the envelope
functions that are chosen. Different alternatives are explored in the paper. Moreover, the model can also be inverted. This
inverted model allows obtaining the force values from the tactile sensor output while reducing the errors caused by
hysteresis. Since implementations of tactile sensors usually have the electronics close to the raw sensor, and this
hardware is also commonly based on a microcontroller or even on a FPGA, it is possible to add the algorithms presented
in this paper to the set of compensation and calibration procedures to run in the smart sensor.
Tactile sensors have increasing presence in different applications, especially in assistive robotics or medicine
and rehabilitation. They are basically an array of force sensors (tactels) and they are intended to emulate the human skin.
Large sensors must be implemented with large area oriented technologies like screen printing. The authors have
proposed and made some piezoresistive sensors with this technology. They consist of a few layers of conductive tracks
to implement the electrodes and elastomers to insulate them, on a polymer substrate. Another conductive sheet is placed
atop the obtained structure. Pressure distribution in the interface between this conductive sheet and the electrodes has a
direct impact on the sensor performance. The mechanical behavior of the layered topology with conductive tracks,
elastomers and polymers must be studied. For instance, the authors have observed experimentally the existence of
pressure thresholds in the response of their sensors. Finite element simulations with COMSOL explain the reason for
such thresholds as well as the dependence of the pressure distribution profile on the properties of the materials and the
geometry of the tactel. This paper presents results from these simulations and the main conclusions that can be obtained
from them related to the design of the sensor.
Many artificial skins for robotics are based on piezoresistive films that cover an array of electrodes. Local preprocessing
is a must in these systems to reduce errors and interferences and cope with the large amount of data provided by the
sensor. This paper presents circuitry based on an FPGA to implement the interface to the artificial skin. The approach consists
of a direct connection. The analog to digital conversion procedure is simple. It consists of measuring the discharging
time of a capacitor through the resistance we want to read. This first proposed approach needs isolated tactels, so the raw
sensor has to be fabricated in this way. If the tactile array is large, the strategy is not feasible. For instance, up to 288 pins
are required to implement the interface with an array of 16x16 tactels. The proposal of this work for this case is to replace
passive integrators by active ones. The result is a circuitry that allows the cancellation of interferences due to parasitic resistors
and the sharing of the addressing tracks. Moreover, the FPGA allows the processing of data from the tactile sensor at
a very high rate. This is because the high number of I/O pins of the device allows the conversion of many channels (in our
case one per column) in parallel. The internal processing of the tactile image can also be done in parallel. This means we
could be able to respond to very high demanding tasks in terms of dynamic requirements, like slippage detection. This also
means we can run complex algorithms at real time, so a smart, programmable and powerful sensor is obtained.
This paper presents results from a few tactile sensors we have designed and fabricated. These sensors are based on a
common approach that consists of placing a sheet of piezoresistive material on the top of a set of electrodes. If a force is
exerted against the surface of the so obtained sensor, the contact area between the electrodes and the piezoresistive material
changes. Therefore, the resistance at the interface changes. This is exploited as transconduction principle to measure forces
and build advanced tactile sensors. For this purpose, we use a thin film of conductive polymers as the piezoresistive material.
Specifically, a conductive water-based ink of these polymers is deposited by spin coating on a flexible plastic sheet,
giving as a result a smooth, homogeneous and conducting thin film on it. The main interest in this procedure is it is cheap
and it allows the fabrication of flexible and low cost tactile sensors. In this work we present results from sensors made with
two technologies. First, we have used a Printed Circuit Board technology to fabricate the set of electrodes and addressing
tracks. Then we have placed the flexible plastic sheet with the conductive polymer film on them to obtain the sensor. The
result is a simple, flexible tactile sensor. In addition to these sensors on PCB, we have proposed, designed and fabricated
sensors with a screen printing technology. In this case, the set of electrodes and addressing tracks are made by printing an
ink based on silver nanoparticles. There is a very interesting difference with the other sensors, that consists of the use of an
elastomer as insulation material between conductive layers. Besides of its role as insulator, this elastomer allows the modification
of the force versus resistance relationship. It also improves the dynamic response of the sensor because it implements
a restoration force that helps the sensor to relax quicker when the force is taken off.
Artificial sensitive skins are intended to emulate the human skin to improve the skills of robots and machinery in complex unstructured environments. They are basically smart arrays of pressure sensors. As in the case of artificial retinas, one problem to solve is the management of the huge amount of information that such arrays provide, especially if this information should be used by a central processing unit to implement some control algorithms. An approach to manage such information is to increment the signal processing performed close to the sensor in order to extract the useful information and reduce the errors caused by long wires. This paper proposes the use of voltage to frequency converters to implement a quite straightforward analog to digital conversion as front end interface to digital circuitry in a smart tactile sensor. The circuitry commonly implemented to read out the information from a piezoresistive tactile sensor can be modified to turn it into an array of voltage to frequency converters. This is carried out in this paper, where the feasibility of the idea is shown through simulations and its performance is discussed.
This paper presents a thermopneumatic actuator to build large tactile displays as well as a smart activation circuitry to study and improve its performance. Since the main drawback of large tactile screens in the market is their cost, this proposal is intended to reduce the price because of the simplicity of the actuator and the potential low cost assembling. A small display with 4 x 4 taxels and 2.54mm of distance between centres has been built to show the viability of the proposal. Furthermore, a smart actuation strategy is implemented where the heater element (a diode) is also used as sensor in a feedback control loop that improves the dynamic response. Such strategy consists in sensing the voltage drop in the diode to measure its temperature, thus it can be heated up quickly without being destroyed because power supply is decreased once the target temperature is reached. We have measured rise times around 2 seconds and fall times around 4 seconds, while the maximum force and stroke are above 10grams (0.1N) and 1mm respectively. The obtained results are good, specially to implement a large tactile screen. Power consumption is high, but it could be lower if latching mechanisms are used to keep the taxel active without power supply.
The interest in tactile sensors is increasing as their use in complex unstructured environments is demanded, like in telepresence, minimal invasive surgery, robotics etc. The matrix of pressure data these devices provide can be managed with many image processing algorithms to extract the required information. However, as in the case of vision chips or artificial retinas, problems arise when the array size and the computation complexity increase. Having a look to the skin, the information collected by every mechanoreceptor is not carried to the brain for its processing, but some complex pre-processing is performed to fit the limited throughput of the nervous system. This is specially important for high bandwidth demanding tasks. Experimental works report that neural response of skin mechanoreceptors encodes the change in local shape from an offset level rather than the absolute force or pressure distributions. This is also the behavior of the retina, which implements a spatio-temporal averaging. We propose the same strategy in tactile preprocessing, and we show preliminary results when it faces the detection of the slip, which involves fast real-time processing.