sensors Article
Design and Characterization of a Three-Axis Hall Effect-Based Soft Skin Sensor Tito Pradhono Tomo 1, *, Sophon Somlor 1 , Alexander Schmitz 1 , Lorenzo Jamone 2 , Weijie Huang 1 , Harris Kristanto 1 and Shigeki Sugano 1 1
2
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Department of Modern Mechanical Engineering, School of Creative Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan;
[email protected] (S.S.);
[email protected] (A.S.);
[email protected] (W.H.);
[email protected] (H.K.);
[email protected] (S.S.) Instituto de Sistemas e Robótica, Instituto Superior Técnico, Lisbon 1049-001, Portugal;
[email protected] Correspondence:
[email protected]; Tel.: +81-3-5286-3264; Fax: +81-3-5272-0948
Academic Editors: Yajing Shen, Lianqing Liu, Ning Xi, Wen Jung Li and Xin Zhao Received: 12 February 2016; Accepted: 31 March 2016; Published: 7 April 2016
Abstract: This paper presents an easy means to produce a 3-axis Hall effect–based skin sensor for robotic applications. It uses an off-the-shelf chip and is physically small and provides digital output. Furthermore, the sensor has a soft exterior for safe interactions with the environment; in particular it uses soft silicone with about an 8 mm thickness. Tests were performed to evaluate the drift due to temperature changes, and a compensation using the integral temperature sensor was implemented. Furthermore, the hysteresis and the crosstalk between the 3-axis measurements were evaluated. The sensor is able to detect minimal forces of about 1 gf. The sensor was calibrated and results with total forces up to 1450 gf in the normal and tangential directions of the sensor are presented. The test revealed that the sensor is able to measure the different components of the force vector. Keywords: tactile; skin; sensor; magnetic
1. Introduction Tactile sensors are crucial for a safe and robust interaction of a robot with its environment. They provide the most direct measurements of the contact forces during planned and accidental contacts. In order to appropriately react to contact forces, it is beneficial if the force sensors are distributed in the robot skin and measure not only normal forces, but also shear forces. Moreover, soft skin is important for softening impact forces and also for robust object grasping. Several studies have been conducted in recent years to develop a distributed tactile sensor for robot skin [1]. For example, a soft capacitive-type sensor that could measure force in 3-axis was introduced in [2]. Although this sensor had high sensitivity and could measure normal and shear forces, each sensor required space of approximately 13 mm ˆ 13 mm (from the center of one sensor to another). Moreover, the manufacturing required a lot of manual work. In this paper we present a Hall effect–based tactile sensor that can measure three-directional force data in limited space. It is both physically small and easy to produce. We evaluate the feasibility of measuring 3-axis force while maintaining a soft exterior for safe interactions. While in previous work [3] we presented preliminary results obtained with the sensor, the current paper provides a detailed sensor characterization. In particular, drift due to temperature changes and the hysteresis in the sensor measurements are analyzed. Furthermore, a calibration to counteract crosstalk between the axes and to extract more precise force vector measurements is provided. Moreover, the design of a printed circuit board (PCB) is presented to show how 16 chips (each measuring 3-axis force) can be placed on a 20 ˆ 23–mm-sized PCB. Sensors 2016, 16, 491; doi:10.3390/s16040491
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The rest of this paper is organized as follows. In Section 2 we provide a review of related tactile sensors. Section 3 describes the sensor principle and the production process. Section 4 presents the experimental procedure that was used to evaluate the sensor and Section 5 shows the results. Section 6 shows a PCB for distributed sensing, and Section 7 draws conclusions and presents future work. 2. Related Works There are many sensing principles which can be employed for tactile sensing [4]. This review will focus on sensors that are capable of measuring normal as well as shear forces in robotic skin. Touchence [5] sells a thin, small-sized 3-axis tactile sensor based on MEMS piezoelectric elements, but the sensor is rigid and the necessary additional electronics are bigger than the sensor itself. A small-sized optical sensor that can measure both normal and shear forces was already proposed more than 10 years ago in [6], but to the best of the authors’ knowledge it has not been integrated in a robotic system yet. Optical 3-axis sensors have also been integrated into soft sensor flesh [7], and those sensors have recently been made commercially available by Touchence as well. A smaller (10 mm wide and 8 mm high) but stiffer optical sensor that can measure the force vector is currently available from OptoForce [8]. An implementation of four tri-axial sensors for a robotic fingertip is presented in [9], and 3-axis F/T (force/torque) sensors were also integrated in the soft skin of the robot Macra [8], both based on strain-gauges. A capacitive 3-axis sensor embedded in soft silicone is presented in [2]. The idea of using Hall effect sensors and magnets to measure a tactile response was originally proposed in [10,11], where only preliminary prototypes were presented, and then this was not investigated anymore until recently [12–16]. In [14], Hall effect–based tactile sensors are integrated on a robot hand and used in object classification experiments; a full characterization of the sensor and more real world experiments are reported in [15]. However, the sensor is based on one-dimensional (1D) Hall effect sensing, and therefore only normal forces can be measured. The work in [12] instead proposes a three-dimensional (3D) sensor, with a design similar to the one we present; however, no accurate characterization is reported, and therefore it is not easy to evaluate the quality of the measurements. The work described in [13,16] is more mature, and it has been successfully applied to real robotic scenarios; however, even though many simulation analyses are presented, this work also lacks a complete characterization of the real sensor. Moreover, the design they propose (with a rubber dome and four Hall effect sensors) imposes constraints on the minimum size of the whole system. A magnetic-based tactile sensor for fingertips has been commercially produced [17]. However, the output signal from this sensor has to be amplified first before it can be read by a microcontroller. The amplifier has a rather big size, meaning that a lot of space is required for integrating this device into a robot. Instead, the current paper uses a single small-sized chip with digital output and the surface of the sensor is flat. Only a magnet embedded in soft silicone is required in addition in order to measure 3-axial forces. 3. Sensor Description The sensor described in this paper is easy to produce and requires only a few tools. This section describes the sensor structure as well as the production process. 3.1. Sensor Concept The force vector can be detected by measuring a magnetic field change. To achieve that, a magnetometer (MLX90393) from Melexis [18] is used. A single MLX90393 chip is capable of providing 3-axis magnetic data and temperature data through the I2C fast mode protocol (four wires). The chip is mounted on a printed circuit board (PCB). We embedded the chip below a soft material, specifically silicone rubber, and implanted a small magnet above it as shown in Figure 1. The soft material acts as a compliant layer, and also transmits the force applied on the top surface. As a result, the small magnet will be displaced from its initial position when force is applied, causing a magnetic field
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magnetic field change. For the experiments in this paper, a PCB with one single chip is used. Section Sensors 2016, 16, 491 3 of 10 VI of this paper shows how multiple chips can be implemented on one PCB. change. For the experiments paper, a in PCB one single chip used.chip Section 6 of this paper magnetic field change. For in thethis experiments thiswith paper, a PCB with oneissingle is used. Section shows how multiple chips can be implemented on one PCB. VI of this paper shows how multiple chips can be implemented on one PCB.
Figure 1. Conceptual Conceptual design and the molding process(right). (right). Liquid silicone rubber was Figure 1. design (left) process (right). (a) Liquid silicone rubber Figure 1. Conceptual design(left) (left)and and the the molding molding process (a)(a) Liquid silicone rubber was was poured intointo the the molding cast; (b) AAsmall small magnet wasplaced placedinside inside the hole; (c) More More liquid silicone poured molding cast; (b)A smallmagnet magnet was thethe hole; (c) More liquid silicone poured into the molding cast; (b) was placed inside hole; (c) liquid silicone rubber waswas poured above the first layer to cover thesmall smallmagnet. magnet. rubber poured above the firstlayer layerto tocover cover the the rubber was poured above the first small magnet.
3.2. Soft Outer Layer 3.2. Soft 3.2. Soft Outer Outer Layer Layer following steps requiredfor for the the molding process. First, an MLX90393 chipchip is placed at The The following steps areare required molding process. First, MLX90393 is placed at The following steps are required for the molding process. First, an an MLX90393 chip is placed at the the middle of a molding cast, supported with four guidance points and double-sided tape. The chip the middle of a molding cast, supported with four guidance points and double-sided tape. The chip middle of a molding supported with Supersoft four guidance points and double-sided tape.Please The chip is covered by liquidcast, silicone rubber (Ecoflex from Smooth-On, shore hardness 00-30). is covered by liquid silicone rubber (Ecoflex Supersoft from Smooth-On, shore hardness 00-30). Please is covered byoptimal liquidmaterial siliconeselection rubber and (Ecoflex Supersoft from Smooth-On, shore hardness note that optimization of the thickness of the compliant layer is not00-30). note that optimal material selection and optimization of the thickness of the compliant layer is not Please that optimal selection and optimization ofthe theposition thickness of magnet the compliant layer is thenote focus of this paper.material To distribute the magnetic field evenly, of the should be the focus of this paper. To distribute the magnetic field evenly, the position of the magnet should be centered above the chip. A guidance lid (Figure 1a) is used to create a hole for placing a small magnet not the focus of this paper. To distribute the magnetic field evenly, the position of the magnet should be centered above the chip. A guidance guidance lid (Figure (Figure 1a) is is used used to create hole for aa small magnet in theabove center.the Thechip. magnet for the current implementation is ato Neodymium magnet coated with nickel centered A lid 1a) create aa hole for placing placing small magnet in the center. The magnet for the current implementation is a Neodymium magnet coated with nickel (Nd-Fe-B) with a dimension of 2 mm × 2.5 mm × 1.7 mm. After the first layer of silicone has cured, in the center. The magnet for the current implementation is a Neodymium magnet coated with nickel the magnet insideof the2 hole, and rubber isfirst usedlayer to cover it. The silicone (Nd-Fe-B) withisaa placed dimension mm ˆ × 2.5 mm × 1.7 mm. the of (Nd-Fe-B) with dimension of 2 mm 2.5more mmliquid ˆ 1.7silicone mm. After After the first layer of silicone silicone has has cured, cured, layer above the PCB is 8 mm thick overall, with liquid the small magnetrubber covered by approximately 2The mm silicone of the magnet is placed inside the hole, and more silicone is used to cover it. the magnet is placed inside the hole, and more liquid silicone rubber is used to cover it. The silicone as inPCB Figure In our experiments there wassmall a good bond between the and second layer layersilicone, above the the is 882.mm byfirst approximately mm of of layer above PCB is mm thick thick overall, overall, with with the the small magnet magnet covered covered by approximately 22 mm of silicone. The silicone covers an area of 55 mm × 55 mm.
silicone, as as in in Figure Figure 2. 2. In layer silicone, In our our experiments experiments there there was was aa good good bond bond between between the the first first and and second second layer of silicone. The silicone covers an area of 55 mm × 55 mm. of silicone. The silicone covers an area of 55 mm ˆ 55 mm.
Figure 2. The prototype of the Hall effect–based skin sensor.
Figure 2. The prototype of the Hall effect–based skin sensor. sensor.
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4. Experimental Setup 4. Experimental Setup Three experiments were conducted to understand the characteristics of the sensor. This section Three were conducted to understand the characteristics oftests. the sensor. This section explains theexperiments experimental setups and procedures that were used during the explains the experimental setups and procedures that were used during the tests. 4.1. Temperature Drift Test 4.1. Temperature Drift Test This test studies the effect of thermal drift on the sensor reading. The skin sensor was placed This test studies the effect of thermal drift on the sensor reading. The skin sensor was placed inside an oven along with a Sparkfun TMP102, which is an I2C temperature sensor for measuring the inside an oven along with a Sparkfun TMP102, which is an I2C temperature sensor for measuring the temperature inside the oven during the test. The MLX90393 chip also includes a temperature sensor. temperature inside the oven during the test. The MLX90393 chip also includes a temperature sensor. The experiment started with the room temperature of 27 ˝°C, then the sensor was heated up until the The experiment started with the room temperature of 27 C, then the sensor was heated up until the skin sensor reached 40 °C. Afterwards, the oven was turned off and the door of the oven was opened skin sensor reached 40 ˝ C. Afterwards, the oven was turned off and the door of the oven was opened to let the temperature drop to around 30 ˝°C. The temperature value and the skin sensor’s readouts to let the temperature drop to around 30 C. The temperature value and the skin sensor’s readouts were recorded using Arduino Due, stored in an SD (secure digital) card. were recorded using Arduino Due, stored in an SD (secure digital) card. 4.2. Hysteresis Test 4.2. Hysteresis Test A viscoelastic material such as silicone can introduce hysteresis in the sensor’s force A viscoelastic material such as silicone can introduce hysteresis in the sensor’s force measurements. measurements. To evaluate the hysteresis, the skin sensor was placed on top of an acrylic platform To evaluate the hysteresis, the skin sensor was placed on top of an acrylic platform table tilted 45 degrees table tilted 45 degrees in the y-axis direction. The sensor was pushed for 5 min with a load of 1450 gf in the y-axis direction. The sensor was pushed for 5 min with a load of 1450 gf (the maximum load that (the maximum load that our experimental setup can achieve). To perform this, a voice coil motor our experimental setup can achieve). To perform this, a voice coil motor (VM5050-190 from Geeplus), (VM5050-190 from Geeplus), a linear bushing, an aluminum shaft adapter, a six-axis force/torque a linear bushing, an aluminum shaft adapter, a six-axis force/torque (F/T) sensor (Nano1.5/1.5 from (F/T) sensor (Nano1.5/1.5 from BL Autotech) for monitoring the pushing force during the experiment, BL Autotech) for monitoring the pushing force during the experiment, and a 30 ˆ 30 mm acrylic push and a 30 × 30 mm acrylic push plate, which is used to push on the proposed sensor, were utilized. plate, which is used to push on the proposed sensor, were utilized. The configuration for this test can The configuration for this test can be seen in Figure 3. Two microcontrollers were required due to the be seen in Figure 3. Two microcontrollers were required due to the different input voltage of our sensor different input voltage of our sensor (3.3 V) and the F/T sensor (5 V). The data from both sensors were (3.3 V) and the F/T sensor (5 V). The data from both sensors were recorded into the SD cards installed recorded into the SD cards installed on Arduino Due and Uno with the synchronized sampling rate on Arduino Due and Uno with the synchronized sampling rate of 100 Hz in our experiments (the of 100 Hz in our experiments (the maximum sampling rate of the Hall effect sensor is about 240 Hz maximum sampling rate of the Hall effect sensor is about 240 Hz to measure all three axes). Finally, the to measure all three axes). Finally, the voice coil motor applied no force on the sensor for one minute, voice coil motor applied no force on the sensor for one minute, and afterwards the acrylic push plate and afterwards the acrylic push plate was retracted. The silicone is sticky, and therefore a force in the was retracted. The silicone is sticky, and therefore a force in the minus z direction is recorded when the minus z direction is recorded when the acrylic push plate is removed. acrylic push plate is removed.
Experiment setup setup used used in in this paper. The The right right side shows the addition of the adjustable Figure 3. Experiment angle tilt stage and the angle push plate, in particular the 30-degree setup where the stage is adjusted to 30 degrees and the 30-degree push plate is used.
4.3. Load Load Test To calibrate sensor andand to evaluate its capability of tri-axial measurement, two experiments calibratethe the sensor to evaluate its capability of force tri-axial force measurement, two were conducted. The first experiment was a normal force whereforce multiple magnitudes of normal force experiments were conducted. The first experiment was atest normal test where multiple magnitudes
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of normal force were applied on the sensor’s top surface. In the second experiment, the sensor was pushed with both normal and shear force in different angles and with different force magnitudes. The configuration for this experiment was similar to the hysteresis test. In the normal force experiment, the skin sensor was mounted directly on the flat and sturdy X-Y table. In the shear force experiment, the sensor was mounted on an adjustable angle tilt stage (Figure 3). This acrylic stage was fixed to the X-Y table. The angle can be adjusted in three different positions that are 15, 30, and 45 degrees, and corresponding acrylic push plates with the same angles were used. In both the normal and shear force experiments, the sensor was pushed by the voice coil motor with a stepwise force and its magnitude was increased every 10 seconds. The applied force was ranging from approximately 70 gf to 1450 gf. A Savitzky-Golay filter was utilized to filter all data (polynomial order = 4, frame size = 21). We performed the normal force test and the shear force tests with 15, 30, and 45 degree, in four directions (+/´ x/y direction). 5. Results and Discussion 5.1. Thermal Drift Evaluation From Figure 4 it can be clearly seen that the Hall effect sensor measurements change with the changing temperature, even though the temperature change measured by the chip was slower than the external temperature. A possible explanation for the change in the Hall effect measurements is an expansion of the silicone packaging with higher temperature. The test also revealed that the sensor reading in the z-axis was the most affected by the temperature change, but also the x-axis and y-axis measurements slightly changed; a closer look reveals that the y-axis is more affected than the x-axis. This is in accordance with the results presented in Section 5.3, which show that changes in the z-axis also affect the x-axis and y-axis, which might be due to a slightly misaligned magnet. The graph shows that the sensor changes are proportional to the temperature change measured by the chip, meaning that temperature compensation can possibly be performed. A linear regression was conducted to find the coefficient k for calibrating the sensor’s outputs. We selected a Huber robust model for this task. The temperature compensation was calculated as follows: Si,T “ Si ´ k i ˆ ∆ST (1) where: ‚ ‚ ‚
i is each axis of the skin sensor (x, y and z). Si and Si,T are the skin sensor readout and compensated value, respectively. ∆ST is the temperature change measured by the MLX90393 built-in temperature sensor.
To evaluate the temperature compensation performance, another test was conducted. This time, the temperature was raised to 35 ˝ C. Figure 5 shows a comparison between the sensor’s readout before and after the compensation was applied. A moving average of the temperature was used for the compensation. After being compensated, the z-axis maximum value was around 600 digits (over a full scale of 65,500 digits), which corresponds to 120 g in our experiments (contact size 30 ˆ 30 mm). Further improvements are likely possible by employing a high-pass filter. Furthermore, small steps can be seen on Sy and Sz . The cause of those is not clear to the authors and will be further investigated in future work.
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Figure 5. A comparison between the sensor’s readout and after temperature compensation was Figure readoutbefore Figure 5. 5. A comparison between the sensor’s readout before and after temperature compensation was applied. The right figure also shows the moving average of the sensor temperature, which was used applied. applied. The The right right figure figure also also shows shows the the moving moving average average of of the the sensor sensor temperature, temperature, which which was was used used for calibrating the sensor. for calibrating the sensor. for calibrating the sensor.
5.2. Hysteresis Evaluation 5.2. Hysteresis Evaluation As expected, there is hysteresis in the sensor measurements. In the result presented in Figure 6, As expected, inin Figure 6, 6, it expected, there thereisishysteresis hysteresisininthe thesensor sensormeasurements. measurements.InInthe theresult resultpresented presented Figure it took about one minute for the sensor to reach its quasi-static state, both while loading and took about one one minute for the to reach quasi-static state, both while loading and unloading it took about minute forsensor the sensor toits reach its quasi-static state, both while loading and unloading the sensor. The x-axis, which was not loaded, showed only a minor drift. Please note that the sensor. the Thesensor. x-axis, The which was which not loaded, showed only a minor drift. Pleasedrift. note Please that annote optimal unloading x-axis, was not loaded, showed only a minor that an optimal soft material selection was not the focus of this study, and the hysteresis can probably be soft materialsoft selection was not the focus of this study,of and the hysteresis canhysteresis probably be with an optimal material selection was not the focus this study, and the canreduced probably be reduced with different materials, for example closed-cell foams. different materials, for example closed-cell foams. reduced with different materials, for example closed-cell foams.
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5.3. 5.3.Load LoadTests Tests and and Calibration Calibration The fromthe theload load test be seen in Figure 7. Figure 7a,b the show Hall effect and The results from test cancan be seen in Figure 7. Figure 7a,b show Hallthe effect and reference reference force sensorrespectively, readout, respectively, only a normal forceEven is applied. force sensor readout, when only when a normal force is applied. thoughEven onlythough normal only force normal force the wasHall applied, Hallalso effect sensora also detected magnetic field change in the effect y-axis.is was applied, effectthe sensor detected magnetic fieldachange in the y-axis. A related A related effectinisSection also described insuspect Sectionthat 5.1,the and we suspect thatsmall the orientation small also described 5.1, and we orientation of the magnet wasof notthe perfectly magnet aligned with theFurthermore, sensor and caused this. is Furthermore, as silicone is forces soft but alignedwas withnot theperfectly sensor and caused this. as silicone soft but incompressible, in incompressible, forces in one axis can cause movements anothermoves direction, the silicone moves one axis can cause movements in another direction, as theinsilicone awayasfrom the pressure. awayFigure from the 7c pressure. shows the Hall effect sensor response when a 45-degree shear force is applied in the Figure shows no theforce Hall was effectapplied sensor in response when a 45-degree shearfrom force is measurements applied in the yy-axis. Even7cthough the x-axis, as can be also seen the of axis. Even though noinforce was applied ineffect the x-axis, candetected be also seen from the measurements the reference sensor Figure 7d, the Hall sensorasalso a small magnetic field changeof in the sensor Furthermore, in Figure 7d, the the y-axis Hall effect sensorsensor also detected a small magnetic fieldthe change the reference x-axis direction. Hall effect measurements are bigger than z-axis in the x-axis direction. Furthermore, theiny-axis Hall effect sensor Due measurements are bigger the measurements, even though the force the z-axis was bigger. to this cross-talk and than different z-axis measurements, the aforce in the was z-axis was bigger. Due to this cross-talk and magnitude of the skin even sensorthough response, calibration performed. different of the skin sensor response, a calibration was from performed. We magnitude used different models to calculate the x, y and z forces the Hall effect sensor values, different models calculate thesensor x, y and z forces from the effectthe sensor values, withWe theused measurements of thetosix-axis F/T as the reference. To Hall calculate parameters with thecalibration, measurements of thefrom six-axis sensor asused. the reference. calculatepurpose, the parameters fornew the for the datasets all F/T angles were For the To evaluation we used calibration, datasets from all angles were used. For the evaluation purpose, we used new datasets datasets that were not used for the calibration. Robust Huber regression was used (MATLAB function that were not used forsquares the calibration. Huber regression used (MATLAB function LinearModel.fit); least regression Robust performed nearly the samewas as the robust Huber regression. LinearModel.fit); least squares regression performed nearlyas thecan same as theby robust Huber regression. A quadratic model performed better than a linear model, be seen higher R-square values A better than linear model, as can seen by higher R-square in inquadratic Table 1. model Also, aperformed neural network (one ahidden layer with 20be hidden units) was trainedvalues with the Table Also, adata neural hidden layer with 20 hidden of units) was trained with the same same 1. training thatnetwork we used (one for approximating the parameters the linear or quadratic equation. training data that weperformed used for approximating thecase parameters ofnormal the linear or quadratic The The neural network better for the test with only force, but overallequation. the quadratic neural network performed for the testresult case with force, but overall theinquadratic equation performed best. better The calibration usingonly the normal quadratic model is shown Figure 8. equation performed best. The calibration result quadratic model shown in Figure The The graphs show the comparison between theusing forcethe detected using the is F/T sensor and the8.force graphs show the comparison between the force detected using the F/T sensor and the force calculated calculated using the skin sensor. A good correspondence between the measurements can be observed, using the biggest skin sensor. A goodincorrespondence measurements can be observed, with the with the differences the normal loadbetween case for the z-axis. biggest in the normal load case for the z-axis. Asdifferences a final evaluation, the minimum detectable load was evaluated. Rubber weights with a As a of final evaluation, theplaced minimum load wasfound evaluated. Rubber weights a diameter about 1 cm were on thedetectable sensor and it was that a force of about 1 gfwith in the diameter of aboutsensor 1 cm were placed on that the sensor and than it wasthe found that anoise forceof ofthe about 1 gf as in can the zz-axis produced measurements are higher observed sensor, be axis measurements that are higher than the observed noise of the sensor, as can be seenproduced in Figure sensor 9. seen in Figure 9.
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Uncalibrated skin sensor 6-axis F/T sensor8 of 10 5000 1000 8 of 10 Fx F/T sensor 6-axis Uncalibrated skin sensor 6-axis F/T sensor 1000 1500 5000 1000 500 Fy 6-axis 6-axis F/T sensor 0 Uncalibrated skin sensor Fx F/T sensor 1500 5000 1000 F 500 1000 z 500 0 FFxy 0 -5000 1000 F 0 500 500 Fyz 0 -5000 -5000 F 5000 -500 z -10000 0 -500 S -1000 -5000 x 0 Fx -1000 -500 -10000 -4000 -2000 0 -500 SSy -15000 -1000 F x -1500 -500 Fyx -1500 -1000 -6000 -10000 -4000 -2000 SSS F zxy -15000 -1000 z -1500 FFxy -1000 -8000 -20000 -2000 -2000 -1500 -60000 -4000 20 40 60 80 0 20SS 40 60 80 0 20 40 60 80 0 20 40 60 80 -15000 z yTime FFzTime (s) Time (s) (s) Time (s) -1500 y -1500 -8000 -20000 -2000 -6000 -2000 S 0 20 40 60 80 0 (c) 20 40 60 80 0 (b) 20 40 60 80 0 (d) 40 60 80 (a) F20 z z Time (s) Time (s) Time (s) Time (s) -8000 -20000 -2000 -2000 0 20 40 sensor’s 60 80 readout (a) 0 from 20 40 60 80 (b) when 0 and 20 40 corresponding 60 80 0 only 20 40 60 80 (a)The (b)the (c) (d)normal Figure 7. force F/T sensor (s) sensor’s readout (a) and TimeF/T (s) sensor (b) when onlyTime (s) Figure 7.Time The the(s)corresponding force from normal Time
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force applied; The (c) and from F/T sensor (d) when (b) the (c) force (d) forceisis(a) Thesensor’s sensor’sreadout readout (c)corresponding andthe the corresponding corresponding forcesensor from (b) F/T sensor (d) when Figure 7.applied; The sensor’s readout (a) and force from F/T when only normal 45-degree shear force is applied in the y-direction. 45-degree shear force is applied in the y-direction. force is7.applied; The readout sensor’s (a) readout (c)corresponding and the corresponding force from(b) F/Twhen sensor (d)normal when Figure The sensor’s and the force from F/T sensor only 45-degree shear force is applied in the y-direction. Calibrated sensor using quadratic regressionforce from F/T sensor (d) when force issensor applied; The sensor’s (c) and the corresponding Calibrated using quadratic regression readout Calibrated sensor using quadratic regression 500 500 500 45-degree shear force is applied in the y-direction. Calibrated sensor using quadratic regression
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500 0 0 500 Calibrated sensor using quadratic regression Calibrated sensor using quadratic regression F F x x 5000 5000 -500 -500 Fy F y F F 0 Fx Fzx 0 z -500 -1000 -500 -1000 F F SF y SFxy x,c x x,c F F -500 -500 z -1000 -1500 -1000 SFy,c -1500 SFyz y y,c S S x,c S x,c F F Sz z,c z -1000 -1000 z,c -1500 -2000 S -1500 S -2000 0 40 60 S y,c20 S y,c20 0 40 60 x,c x,c Time (s) Sz,c Time (s) S -1500 S z,c -1500 -2000 S y,c -2000 y,c 0 20 (c) 40 60 0 20 (b) 40 60 Sz,c Time (s) S Time (s) z,c -2000 -2000 0 20 40 60 0 20 (b) 40 60 (c) 45-degree (x-axis (c) 45-degree (y-axis direction); direction) force Time (s) Time (s)
calibration result. Sx,c, Sy,c and Sz,c are the calibrated skin sensor measurements. (a)Normal (b) (c) Figure 8. (a) force; (b) 45-degree (y-axis direction); (c) 45-degree (x-axis direction) force Figure 8. (a) Normal force; (b) 45-degree (y-axis direction); (c) 45-degree (x-axis direction) force calibration result. S x,c, Sy,c and Sz,c are the calibrated skin sensor measurements. Figure 8. (a) Normal (b)Sz,c 45-degree (y-axis direction); (c)measurements. 45-degree (x-axis direction) force calibration result. Sx,c ,force; Sy,c and skin sensor 4 are the calibrated calibration result. Sx,c, Sy,c and Sz,c are the calibrated skin sensor measurements. 4
ForceForce (gf) Force (gf) (gf)
Force (gf) Force Force (gf) (gf)
500 0 Calibrated sensor using quadratic regression F x 500 -5000 Fy F Fx 0 -500 z -1000 F SFxy x,c F -500 -1000 -1500 SFyz y,c S SFzx,c z,c -1000 -1500 -2000 S 0 40 60 S y,c20 x,c Time (s) S z,c -1500 S -2000 y,c 0 20 (a) 40 60 S Time (s) z,c -2000 0 40 60 Figure 8.20(a)(a) Normal force; (b) Time (s)
24 2 02 0
-20 0
1 2 3 4 Time (s) -2 0 1 2 3 4 Time Figure 9. The z-axis calibrated sensor (S(s) z,c) when a weight of 1 g (contact area of about -2 measurements 0 1 3 1 cm2) is placed on the sensor at a time of around 2 s.2The calibration is4 slightly incorrect in this case, Time Figure 9. The z-axis calibrated sensor measurements (S(s) z,c) when a weight of 1 g (contact area of about
showing a measurement of 2 gf. This might be partially due to the different contact area than that 1 cm2) is placed on the sensor at a time of around 2 s.(SThe calibration is slightly incorrectarea in this case, Figure 9. z-axis sensor ) when aaweight ofof11gdetect of during the calibration. Nevertheless, can be seen that the sensor can already a 1 garea weight. Figure 9.The The z-axiscalibrated calibrated sensoritmeasurements measurements (Sz,c weight g(contact (contact ofabout about z,c ) when showing a measurement of 2 gf. This might be partially due to the different contact area than that 2 11cm cm2) )isisplaced placedon onthe thesensor sensoratataatime timeof ofaround around22s.s.The Thecalibration calibrationisisslightly slightlyincorrect incorrectininthis thiscase, case, during the calibration. Nevertheless, it can be seen that the sensor can already detect a 1 g weight. showing of This might be different contact Table 1. R-squared value the normal forcedue and shear experiments. showingaameasurement measurement of22gf. gf. Thisfor might bepartially partially dueto tothe theforce different contactarea areathan thanthat that during the calibration. Nevertheless, it can be seen that the sensor can already detect a 1 g weight. during the calibration. Nevertheless, it can be seen that the sensor can already detect a 1 g weight. Table 1. R-squared value for the normal and shear force experiments. Linear + Huber Quadratic + force Huber Feedforward Neural Network
Normal Force 0.8634 0.8925 0.9368 Table 1.Linear R-squared value forQuadratic the normal and shear force experiments. + Huber +force Huber Feedforward Neural Network Shear 45—y 0.8634 0.9418 0.8275 Normal Force Linear 0.8634 0.8925 + Huber Quadratic + Huber Feedforward0.9368 Neural Network Shear 45—x 0.9272 0.9744 0.9644 Shear 45—y 0.8634 0.9418 0.8275 Normal Force 0.8634 0.8925 0.9368 Shear 45—y 45—x 0.9272 0.9744 0.9644 Shear 0.8634 0.9418 0.8275 Shear 45—x 0.9272 0.9744 0.9644
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Table 1. R-squared value for the normal force and shear force experiments.
Normal Force Shear 45—y Shear 45—x
Linear + Huber
Quadratic + Huber
Feedforward Neural Network
0.8634 0.8634 0.9272
0.8925 0.9418 0.9744
0.9368 0.8275 0.9644
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6. Design of PCB for Distributed Sensors 6. Design of PCB for Distributed Sensors A custom PCB (Figure 10) has been designed to integrate 16 MLX90393 chips for detecting A custom PCB (Figure 10) has been designed to integrate 16 MLX90393 chips for detecting distributed force vectors. The PCB has two layers, is only 20 ˆ 23 mm big and has four I2C outputs. distributed force vectors. The PCB has two layers, is only 20 × 23 mm big and has four I2C outputs. The distance of the center of one chip to the next one is 4.7 mm. After the PCB has been produced, in The distance of the center of one chip to the next one is 4.7 mm. After the PCB has been produced, in future work the crosstalk between the sensors will be evaluated. future work the crosstalk between the sensors will be evaluated.
Figure 10. A custom PCB for integrating 16 MLX90393 chips.
7. Conclusions Conclusions This paper characterization of aofHall effect–based soft soft skin skin sensor. The paper presented presentedthe thedesign designand and characterization a Hall effect–based sensor. temperature test test shows thatthat thethe skin sensor’s readout in in the The temperature shows skin sensor’s readout thez-axis z-axisdirection directionwas wasthe the one one mostly temperature changes. changes. Using affected by temperature Using aa built-in built-in temperature temperature sensor, drift compensation was performed. Next, the hysteresis was evaluated. Indeed performed. Indeed there there is is hysteresis hysteresis in in the thesensor sensormeasurements, measurements, which is to be expected due to the use of silicone, which is a viscoelastic material. After the calibration which when applying varying amounts of normal and shear force, the tests showed that the of the sensor, when sensor can measure the components of the force vector. Furthermore, the design of a PCB with 16 3-axis force measurements in limited space is presented. As future work, the crosstalk between those 16 sensors bebe evaluated. Furthermore, a spherical magnet will be used order sensors in inclose closeproximity proximitywill will evaluated. Furthermore, a spherical magnet will be in used in to avoid possible spurious signals on irrelevant axes. TheThe use ofofdifferent order to avoid possible spurious signals on irrelevant axes. use differentmaterials materials or or different potential means means to to reduce reduce the the hysteresis. hysteresis. thicknesses of the packaging will be studied as potential Acknowledgments: This research was partially supported by the JSPS Grant-in-Aid for Scientific Research Research (S) No. 25220005, JSPS JSPS Grant-in-Aid Grant-in-Aid for for Young Young Scientists No. 25220005, Scientists (B) (B) No. No. 15K21443, 15K21443, NEDO NEDO project project No. No. 15657422, 15657422, Research Research Institute for Science and Engineering of Waseda University, the Program for Leading Graduate Schools, “Graduate Institute for Science and Engineering of Waseda University, the Program for Leading Graduate Schools, Program for Embodiment Informatics” of the Ministry of Education, Culture, Sports, Science and Technology, and “Graduate Program[PIEF-GA-2013-628315]. for Embodiment Informatics” of the Ministry of Education, Culture, Sports, Science and Project LIMOMAN Technology, and Project LIMOMAN [PIEF-GA-2013-628315].
Author Contributions: T.P.T. implemented the sensor and performed the experiments; S.So. assisted with implementing the sensor, testing the sensor, and designed the test setup; A.S., L.J. and S.Su. conceived and designed the experiments and provided support. T.P.T. and A.S. wrote the paper. W.H. and H.K. helped in building and testing the sensor. Conflicts of Interest: The authors declare no conflict of interest.
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Author Contributions: T.P.T. implemented the sensor and performed the experiments; S.So. assisted with implementing the sensor, testing the sensor, and designed the test setup; A.S., L.J. and S.Su. conceived and designed the experiments and provided support. T.P.T. and A.S. wrote the paper. W.H. and H.K. helped in building and testing the sensor. Conflicts of Interest: The authors declare no conflict of interest.
Abbreviations The following abbreviations are used in this manuscript: PCB MEMS F/T SD
Printed circuit board Microelectromechanical system Force/torque Secure digital
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