Three-axis Tactile Sensor Research Articles

An Experimental Optical Three-Axis Tactile Sensor for Micro Machines.

This paper described a micro optical three-axis tactile sensor capable of sensing not only vertical force but also horizontal force. The vertical force was detected from the integrated gray scale values of bright pixel emitted from the contact area of conical feelers. The conical feelers were formed on the rubber sheet surface keeping contact with an optical waveguide plate. The horizontal force was detected from the horizontal displacement of the conical feelers. In the experiments, a precise multi-axial loading machine was developed to measure sensing characteristics of the present sensor. It was found that the vertical force was specified uniquely under combined force conditions and that the horizontal force was specified by modifying the relationship between the horizontal force and the horizontal displacement on the basis of vertical force. From the experimental results calibration coefficients were identified to transform the integrated of gray scale values into vertical force and to transform the horizontal displacement into the horizontal force.

1013 光導波路形三軸触覚センサの高精度化

A robotic manipulator equipped an optical three-axis tactile sensor can detect the distribution of not only vertical but also horizontal force. This sensor is composed of a silicone-rubber sheet, an acrylic plate, a CCD camera and a light source. A silicone-rubber sheet has an array of 8×9 sensor cells consisting of columnar feeler and 2-by-2 conical feelers. Since the reflectance of silicone-rubber is naturally low, the contact area between conical feelers and an acrylic plate cannot be accurately identified. Thus we developed a new silicone-rubber sheet with high reflectance by adding aluminum powder into pre-hardened silicone-rubber. In the experiments, we measured the sensitivity of the present sensor equipped aluminum powder doped silicone-rubber sheet. As a result, the sensitivity of the present tactile sensor was enhanced because clearness of contact contour caused identification of contact area to be more precise.

Step-height Discrimination Using a Robotic Manipulator Equipped an Optical Three-axis Tactile Sensor.

A robot makes to be enhanced sensing capability to discriminate surface unevenness of an object by means of equipping an optical three-axis tactile sensor. The single sensor cell of the sensor was comprised of a columnar feeler and 2-by-2 conical feelers. Three-axis force and displacement were estimated from the area-sum and area-difference of contact areas of the conical feelers. To perform surface detection experiments, the optical three-axis tactile sensor was mounted on the wrist of a robotic manipulator having five degrees of freedom. The robotic manipulator rubbed the tactile sensor on three brass plates with step-heights δ=50, 100, 200 μm and a brass plate with no step-height. We proposed the virtual PSD (position detective device) method capable of processing rapidly image data to obtain distributions of three-axis force. Experimental results indicated that the optcal three-axis tactile sensor was able to detect the distribution of the coefficient of friction in spite of existence of step-heights. This tactile sensor was able to detect fine step-heights in the range of from 50 to 200 μm and to detect inclinations of the brass plate in the range of from -0.38 to 0.38°.

Sensing Characteristics of an Optical Three-Axis Tactile Sensor Under Combined Loading.

This paper describes precision enhancement of an optical three-axis tactile sensor capable of detecting both normal force and tangential force. The sensor's single cell consists of a columnar feeler and 2-by-2 conical feelers. We have derived equations to precisely estimate the three-axis force from the area-sum and area-difference of the conical feelers' contact areas by taking into account wrench-length shrinkage caused by a vertical force. To evaluate the equations and determine constants included in the equations, we performed a series of calibration experiments using a manipulator-mounted tactile sensor and a combined load-testing machine. Subsequently. to evaluate the tactile sensor's practicality. it was mounted on the end of a robotic manipulator which rubbed flat specimens such as brass plates with step-heights of δe0.05, 0.1, 0.2 mm and a brass plate with no step-height. We showed from the experimental data that the optical three-axis tactile sensor can detect not only the step-heights but also the distribution of the coefficient of friction, and that the sensor can detect fine plate inclination with accuracy to about ±0.4°.

Silicon three-axial tactile sensor

A novel three-axial tactile sensor based on the differential capacitive principle is presented. The sensor is fabricated using IC processing and bulk-micromachining technology. Normal and shear forces are detected by capacitor arrays under force mesas. Experimental devices show sensitivities of 0.13 pF g −1 to normal forces, and 0.32 pF g −1 to shear forces in a force range of 0–1 g. The device has a spatial resolution of 2.2 mm. Its maximum dynamic response frequency is 162 Hz. The force range and sensitivity can be adjusted by changing the membrane thickness. A dynamic measurement range of more than 100 can be obtained using detection circuits with a resolution of 10 fF.

Implementation of Experimental Three-Axis Tactile Sensor System Applying Optical Waveguide Plate.

The present paper describes the implementation of and experiments on a three-axis tactile sensor applying an optical wave guide plate. The sensor is comprised of a sparse array of columnar feelers and a dense array of conical feelers, which are formed on opposite sides of a silicon rubber sheet. The columnar feelers contact objects while the conical feelers contact the acrylic optical waveguide plate. Three components of a force vector applied to the columnar feeler are identified from contact areas of four conical feelers which are covered by one columnar feeler. Contact points of conical feelers photographed using a CCD camera are transferred into a frame memory board installed in a personal computer and they are memorized as 8-bit patterns. A one-bit pattern is quantized from the 8-bit pattern by utilizing a suitable threshold value; the contact areas of conical feelers are obtained from the total number of picture cells of the one-bit pattern. In evaluation experiments, several combinations of vertical and horizontal forces are applied to the columnar feeler through a probe attached to a three-axis force sensor. The experimental results show that the three components of the force vector can be calculated from the four contact areas, and that hard material is not favorable for the conical feelers but is suitable for columnar feelers.

Tactile Recognition Based on Fuzzy Production Rules Using Robot Hand Equipped with Three-Axis Tactile Sensors.

Tactile Recognition Based on Fuzzy Production Rules Using Robot Hand Equipped with Three-Axis Tactile Sensors.

Tactile Recognition Based on Repetition of Grasping of an Object with a Robot Hand. Calculation Method for Increasing Probability Levels Using Fuzzy Relations.

A new robotic tactile recognition method wherein repetitions of grasping of an object enhanced recognition certainty was presented. To evaluate the certainty, probability levels of recognition were calculated by a fuzzy relational matrix defining similarities between objects. Calculations using various kinds of fuzzy compositions and binary operations required for the iterative evaluation process were compared. Arithmetic sum and product were found to be most suitable, being able to reflect the increase in probability levels. By applying the arithmetic calculations, a new program module for increasing probability levels was implemented. The module was incorporated into the fuzzy production system which was composed of a calculation module for characteristic parameters and an inference module using fuzzy production rules. Three modules were cyclically processed through repetitions of grasping of an object. A series of tactile recognition experiments using a robot hand equipped with three-axis tactile sensors were performed. Consequently, the present system succeeded in recognizing three-dimensional shapes of unknown objects such as an icosahedron and an imperfect sphere, which could not be recognized through only a single grasping.

Design of Three-Axis Tactile Sensor Applying Optical Waveguide Plate Based on FEM Contact Analysis.

The present paper describes a new three-axis tactile sensor applying an optical waveguide plate. The sensor comprises two kinds of feeler arrays attached on opposite sides of a rubber sheet. One is a sparse array of column shaped feelers which contact the object to be recognized, the other is a dense array of cone shaped feelers which maintain contact with the waveguide plate. Since one column feeler under the action of applied force is arranged to press four cone feelers, components of the force vector are identified by the four contact areas of the cone feelers. A series of contact analysis using the nonlinear finite-element method was performed to provide desirable shapes of feelers and optimum Young's moduli of the feelers and the rubber sheet. The present tactile sensor is confirmed to be able to measure three components of the applied force vector. It is found that the sensitivity is affected not by Young's modulus of the column feelers but by that of the cone feelers, and that the sensitivity is proportional to the length of the column feelers, but inversely to the thickness of the rubber sheet.

Tactile Expert System Using a Parallel-Fingered Hand Fitted with Three-Axis Tactile Sensors

In an effort to improve the intelligence of a robot fitted with tactile sensors, we have developed a tactile sensor array which detects the distribution of three applied force vector components. Here, we introduce formulas for basic tactile information such as applied force and moment, centroid of distributed pressure, contact pattern, contact state and mechanical properties, obtained through contact of the tactile sensor with an object. We then produce a tactile expert system which is capable of recognizing the material, shape and stability of the object by means of a reasonably combining the basic tactile information. Recognition experiments show that the system can infer the material and shape of seven objects and that it can control the hand in response to the different kinds of grasping instability.

Tactile Expert System Using a Parallel Finger Hand with Three-Axis Tactile Sensors.

In order to improve the intelligence of a robot with a tactile sensor, we have discussed basic tactile information, such as slippage and the hardness of a grasped object. In this paper, we produce a tactile expert system which can recognize the material and the shape of the object, and the stability of grasping by means of a reasonable combination of the basic tactile information. Also, in order to discuss the validity of the system, we produced a robot hand which has two plate-type fingers with three-dimensional tactile sensors, and then carried out a series of experiments with the hand and the system. Recognition experiments show that the system can infer seven kinds of objects and that it can control the hand in response to the kinds of instability in grasping.

Data processing of tactile information for three-axis tactile sensor.

In order to improve the intelligence of a robot with a sense of touch, we have developed a tactile sensor array which can detect the distribution of the three components of a force vector. The tactile sensor consists of a 6×15 matrix of 3×3 mm sensing sites; each site is made of two single-crystal silicon rings on which semiconductor strain gauges are formed by means of a semiconductor processing technique. In this paper, we have introduced formulas to calculate applied force/moment, a center of distributed pressure, and some parameters of slip and hardness, and then carried out sensing tests in order to validate those formulas. Experimental results show that applied force/moment and the center of distributed pressure can be detected with practical accuracy. Slipping, rolling and rotating states can be distinguished by combinations of the slip parameters. Moreover, mechanical properties can be sensed by means of combinations of the hardness parameters. A lump in a soft object can be recognized using an adequate threshold method.