Optical Three-axis Tactile Sensor Research Articles

Sensitivity-enhancing All-in-type Optical Three-axis Tactile Sensor Mounted on Articulated Robotic Fingers

In a previous study, we developed an all-in-type optical three-axis tactile sensor to address two issues: the first is to be able to use external devices such as a CCD camera and light source; the other is the insensible zone. We miniaturized its whole structure through adoption of a CMOS board camera equipped with LEDs. Since a USB is installed in the CMOS camera as an interface, an additional image processing board is not required. Furthermore, it is equipped with a rubber dome including a sensing element array to remove the insensible zone because rubber is filled in between the sensing elements. However, even if it accepted under around 1-N force, no output of brightness appeared. In this paper, we enhance the characteristic in the low level applied force through improvement of image processing. Furthermore, the present sensor showed higher output level of normal and tangential forces through a series of experiments comparing the present and ordinal three-axis tactile sensors.

Tactile Slippage Analysis in Optical Three-Axis Tactile Sensor for Robotic Hand

This paper presents experimental results of object handling motions to evaluate tactile slippage sensation in a multi fingered robot arm with optical three-axis tactile sensors installed on its two hands. The optical three-axis tactile sensor is a type of tactile sensor capable of defining normal and shear forces simultaneously. Shear force distribution is used to define slippage sensation in the robot hand system. Based on tactile slippage analysis, a new control algorithm was proposed. To improve performance during object handling motions, analysis of slippage direction is conducted. The control algorithm is classified into two phases: grasp-move-release and grasp-twist motions. Detailed explanations of the control algorithm based on the existing robot arm control system are presented. The experiment is conducted using a bottle cap, and the results reveal good performance of the proposed control algorithm to accomplish the proposed object handling motions.

Application of Tactile Slippage Sensation Algorithm in Robot Hand Control System

This paper presents application of a new tactile slippage sensation algorithm in robot hand control system. The optical three-axis tactile sensor is a type of tactile sensor capable of defining normal and shear forces simultaneously. The tactile sensor is mounted on fingertip of robotic hand. Shear force distribution is used to define slippage sensation in the robot hand system. Based on tactile slippage analysis, a new control algorithm was proposed. To improve performance during object handling motions, analysis of slippage direction is conducted. The control algorithm is classified into two phases: grasp-move-release and grasp-twist motions. Detailed explanations of the control algorithm based on the existing robot arm control system are presented. The experiment is conducted using a bottle cap, and the results reveal good performance of the proposed control algorithm to accomplish the proposed object handling motions.

Grasping Strategy and Control Algorithm of Two Robotic Fingers Equipped with Optical Three-Axis Tactile Sensors

This paper presents grasping strategy of robot fingers based on tactile sensing information acquired by optical three-axis tactile sensor. We developed a novel optical three-axis tactile sensor system based on an optical waveguide transduction method capable of acquiring normal and shearing forces. The sensors are mounted on fingertips of two robotic fingers. To enhance the ability of recognizing and manipulating objects, we designed the robot control system architecture comprised of connection module, thinking routines, and a hand/finger control modules. We proposed tactile sensing-based control algorithm in the robot finger control system to control fingertips movements by defining optimum grasp pressure and perform re-push movement when slippage was detected. Verification experiments were conducted whose results revealed that the finger's system managed to recognize the stiffness of unknown objects and complied with sudden changes of the object's weight during object manipulation tasks.

Geometrical Data Extraction Using Interaction Between Objects and Robotic Fingers Equipped with Three-axis Tactile Sensors

If humans want to know geometrical information about certain objects, we can pick them up, push them, pull them or turn them to learn the distance and relationship between the objects and us. Although this tactic is very effective for robots working in unknown environments, it has not always been applied to them because it requires sophisticated tactile sensors to obtain data from the interaction between robotic hands and their environment. On the other hand, we developed a robotic finger equipped with optical three-axis tactile sensors, of which the sensing cell can separately detect normal and shearing forces. A robotic hand equipped with such fingers can explore geometrical data through pushing-pulling, turning and picking up-placing motions as follows. It can acquire the contour of an object with a corrugated shape through scanning the surface with two fingers; it can learn a curved line to fit a cap contour through turning it, even if input finger trajectories are rectangular; it can place an object on a specified location with unknown height (z-coordinate) after measuring the x-y position of the location because it can detect upward slippage occurring between the object and fingers when the object bottom touches the location.

Two-Hand-Arm Manipulation Based on Tri-axial Tactile Data

Tactile sensing ability is important for social robots, which perform daily work instead of persons. The authors have developed a three-axis tactile sensor based on an optical measurement method. Since our optical three-axis tactile sensor can measure distributed tri-axial tactile data, a robot equipped with the tactile sensors can detect not only grasping force but also slippage from its hands. In this paper, the authors have two objectives: one of them is evaluation of the three-axis tactile sensor in actual robotic tasks; the other is to demonstrate effectiveness of tri-axial tactile data for motion control. To accomplish these objectives, the authors have developed a two-hand-arm robot equipped with three-axis tactile sensors. In the robot motion control, we implement a recurrent mechanism in which the next behavior is induced by the tactile data to make the robot accept intention embedded in the environment. Since this mechanism is based on the tactile data, it is easy to apply it to communication between the hand-arms to obtain the best timing for cooperative work. In a series of experiments, the two-hand-arm robot performed object transfer and assembling tasks. Experimental results show that this tri-axial tactile base programming works well because appropriate behavior is induced according to slippage direction.

Object Exploration Using a Three-Axis Tactile Sensing Information

2 Faculty of Mechanical Engineering University Technology MARA, Malaysia Abstract: Problem statement: To advance the robust object recognition of robots, we present an algorithm for object exploration based on three-axis tactile data that is necessary and sufficient for the evaluation of contact phenomena. Approach: The object surface contour is acquired by controlling the finger position so that the normal force, measured by optical three-axis tactile sensors, remains constant as two fingertips slide along the object surface. In this algorithm, when the robot grasps an object, the tangential force increment is checked to judge the initial contact state because it is more sensitive than the normal force. After contact between the fingertips and the object, the normal force is adjusted to remain constant with a tolerant value between the upper and lower thresholds. Results: In the verification test, shape exploration experiments were conducted using a hand-arm robot equipped with our tactile sensor and a hard sinusoidal-shaped wooden object. Experimental results show that the hand-arm robot is capable of gathering the object contour having a concave or convex portion because its finger position controlled by three-axis tactile sensing information follows the object surface. Conclusion/Recommendations: We derive a control algorithm in robot fingers based on time tangential force increment and normal force detection to perform a shape exploration procedure.

Edge Extraction using Image and Three-Axis Tactile Data

Abstract This paper describes a hand-arm system equipped with optical three-axis tactile sensors and a binocular vision sensor. The vision compensates for the limitations of tactile information and tactile sensing, and vice versa. The tactile sensor can obtain geometrical data as real scale, while image data requires calibration to obtain length as a metric unit. Even if stereovision is used, we cannot obtain sufficient precision. In the evaluation test, the robotic hand equipped with tactile sensors traces an object including convex and concave portions to evaluate edge trace precision. Error of distance obtained by the binocular vision is around ± 10 mm when distance between the camera and object is around 600 mm. When the hand-arm robot touches the convex portion of the object, size data obtained by the vision is modified within ± 0.5 mm accuracy. Since the robotic finger is too thick to touch the bottom of the concave, size data of the concave portion obtained by tactile sensing includes relatively large error of around 4 mm. However, the robot finger can follow the contour with ± 0.5 mm accuracy except for the bottom portion. Therefore, vision sensing is not sufficient for precise edge exploration and modification based on tactile sensing is required.

Sensorization of Robotic Hand Using Optical Three-Axis Tactile Sensor: Evaluation with Grasping and Twisting Motions

Problem statement: Sensitization of robot hand is still remaining as crucial issue since most of robot hand systems nowadays are only capable to grasp a predefined specific object. It is still difficult for robot hand system to realize human-like tactile sensation. Some common problems in robot hand system are low accuracy sensing device, sensors are not robust enough for long time work and heavy duties, inconsistence tactile sensing detection and difficulties in control of sensing fusion with robot trajectory. These problems are apparently drawback the progress to commercializing robot hands as real consumer products. Approach: This study presented the application of optical three-axis tactile sensor to robot hand to improve sensitization quality in robotic hand system. The proposed tactile sensor system was designed with compliance modules to communicate with robot hand control system. The sensing principle used in this tactile sensor comparatively provides better sensing accuracy to detect contact phenomena from acquisition of three axial directions of forces. Methodology of force and slippage detection in the tactile sensor system was presented. Accordingly, the optimization of robot hand control algorithm to comply with the tactile sensor system was presented and verified in experiment of grasping and twisting. Results: The tactile sensor presented in this study is capable of detecting normal and shear force simultaneously. The proposed methodology was verified in experiment with paper cup and water, in which the result shows the robot control system managed to respond to the proposed object stiffness distinction parameters and effectively respond to sudden change of object weight during grasping. An experiment of grasping and twisting motions was conducted using a bottle cap. In order to perform simultaneous grasping and twisting tasks, optimization of the control algorithm was conducted with additional parameters to satisfy the desired tasks. Conclusion: Experimental result shows that the robot hand managed to perform grasping and twisting of bottle cap smoothly. The overall results revealed good performance of the proposed optical three-axis tactile sensor system and robot hand control algorithm for future application in a real artificial robot hand. In addition, slippage sensation measured in a robot control system could contribute a better maneuvering of the robot arm-finger system.

Analysis of Tactile Slippage Control Algorithm for Robotic Hand Performing Grasp-Move-Twist Motions

Abstract This paper presents an analysis result of grasp-move-and-twist motions of robotic hands equipped with optical three-axis tactile sensor to evaluate performance of a new control algorithm based on tactile slippage sensation. The optical three-axis tactile sensor is capable of defining normal and shear forces simultaneously. The proposed algorithm consists of robot arm and hand controls based on parameters of normal and shear force, and slippage detection. To improve performance during grasp, move and twist motions, we present analysis of slippage direction and classify the control algorithm in two phases: grasp-move-release and grasp-twist. We present detailed explanation of the control algorithm based on the existing robot arm control system. The experiment is conducted using a bottle cap, and the analysis results show that the slippage control parameters enhanced performance of grasp control in simultaneous robot tasks. Experimental results revealed good performance of the proposed control algorithm to accomplish the proposed grasp-move-and-twist motions.

2A2-C11 Grasping Strategy of Two Robotic Fingers Equipped with Optical Three-Axis Tactile Sensors

2A2-C11 Grasping Strategy of Two Robotic Fingers Equipped with Optical Three-Axis Tactile Sensors

Object exploration and manipulation using a robotic finger equipped with an optical three-axis tactile sensor

To evaluate our three-axis tactile sensor developed in preceding papers, a tactile sensor is mounted on a robotic finger with 3-degrees of freedom. We develop a dual computer system that possesses two computers to enhance processing speed: one is for tactile information processing and the other controls the robotic finger; these computers are connected to a local area network. Three kinds of experiments are performed to evaluate the robotic finger's basic abilities required for dexterous hands. First, the robotic hand touches and scans flat specimens to evaluate their surface condition. Second, it detects objects with parallelepiped and cylindrical contours. Finally, it manipulates a parallelepiped object put on a table by sliding it. Since the present robotic hand performed the above three tasks, we conclude that it is applicable to the dexterous hand in subsequent studies.

An Experimental Optical Three-axis Tactile Sensor Featured with Hemispherical Surface

We are developing an optical three-axis tactile sensor capable of acquiring normal and shearing force to mount on a robotic finger. The tactile sensor is based on the principle of an optical waveguide-type tactile sensor, which is composed of an acrylic hemispherical dome, a light source, an array of rubber sensing elements, and a CCD camera. The sensing element of the silicone rubber comprises one columnar feeler and eight conical feelers. The contact areas of the conical feelers, which maintain contact with the acrylic dome, detect the three-axis force applied to the tip of the sensing element. Normal and shearing forces are then calculated from integration and centroid displacement of the grayscale value derived from the conical feeler's contacts. To evaluate the present tactile sensor, we conducted a series of experiments using an x-z stage, a rotational stage, and a force gauge. Although we discovered that the relationship between the integrated grayscale value and normal force depends on the sensor's latitude on the hemispherical surface, it is easy to modify the sensitivity based on the latitude to make the centroid displacement of the grayscale value proportional to the shearing force. When we examined the repeatability of the present tactile sensor with 1,000 load/unload cycles, the error was 2%.

An Experimental Optical Three-Axis Tactile Sensor Featured with Hemispherical Surface

We are developing an optical three-axis tactile sensor capable of acquiring normal and shearing force, with the aim of mounting it on a robotic finger. The tactile sensor is based on the principle of an optical waveguide-type tactile sensor, which is composed of an acrylic hemispherical dome, a light source, an array of rubber sensing elements, and a CCD camera. The sensing element of silicone rubber comprises one columnar feeler and eight conical feelers. The contact areas of the conical feelers, which maintain contact with the acrylic dome, detect the three-axis force applied to the tip of the sensing element. Normal and shearing forces are then calculated from integration and centroid displacement of the gray-scale value derived from the conical feeler's contacts. To evaluate the present tactile sensor, we have conducted a series of experiments using a y-z stage, a rotational stage, and a force gauge, and have found that although the relationship between the integrated gray-scale value and normal force depends on the sensor's latitude on the hemispherical surface, it is easy to modify the sensitivity according to the latitude, and that the centroid displacement of the gray-scale value is proportional to the shearing force. When we examined repeatability of the present tactile sensor with 1 000 loading-unloading cycles, the respective error of the normal forces was 2%.

A Robotic Finger Equipped with an Optical Three-Axis Tactile Sensor

In the preceding paper we developed an optical three-axis tactile sensor capable of acquiring normal and shearing force, with the aim of mounting it on a robotic finger. Normal force and shearing force applied to the sensing element were detected separately ; when we examined repeatability of the present tactile sensor with 1 000 loading-unloading cycles, the respective error of the normal forces was 2%. In the present paper, the three-axis tactile sensor is mounted on a robotic finger of 3 degrees of freedom to evaluate the tactile sensor for dexterous hands. In a series of experiments, three kinds of experiments are performed. First, the robotic hand touches and scans on flat specimens to evaluate ability of surface condition. Second, it detects contour of parallelepiped and cylindrical objects. Finally, it manipulates a parallelepiped case put on a table by means of sliding on the table. Since the present robotic hand was able to perform the abovementioned three tasks with appropriate precision, we prospected that the hand was applicable to the dexterous hand in the subsequent studies.

A Tactile Recognition System Mimicking Human Mechanism for Recognizing Surface Roughness

A mathematical model was formulated on the basis of results from psychophysical experiments in which human subjects discriminated fine steps on aluminum plates. The mathematical model emulated the real neuron discharge caused when a membrane potential exceeds a threshold. This membrane potential was determined by spatial and temporal summations of postsynaptic potential. To evaluate the mathematical model for surface texture recognition by robots, we performed a series of surface-detection experiments using a robotic manipulator equipped with an optical three-axis tactile sensor. The single sensor cell of this sensor consisted of a columnar feeler and a 2-by-2 array of conical feelers. The three-axis force was calculated from the area-sum and area-difference of the conical feelers’ contact areas. The robotic manipulator rubbed the tactile sensor on four brass plates with step heights of 0, 0.05, 0.1 and 0.2mm. Results showed that the mathematical model could distinguish these step heights in real time.

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 δ=0.05, 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°.

光導波形三軸触覚センサ搭載ロボットによる高速表面走査(OS12 アクチュエータシステム)

An optical three-axis tactile sensor is comprised 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 a columnar feeler and conical feelers. In the present paper, the authors evaluated a new sensing element having a columnar feeler and 8 conical feelers proposed in the previous paper. For the sensing element, normal and shearing forces are calculated from integrated gray scale value and centroid displacement caused by conical feeler's contacts. In the present experiments, the tactile sensor was mounted on an articulated manipulator and the manipulator scanned on precise abrasive paper. It was found that obtained shearing force increased with increase of particle size of the abrasive paper and degreased with increase of scanning velocity. Contrarily, in the case of Teflon tape, shearing force was almost constant in spite of velocity increasing. The above-mentioned results show grinding phenomena discussed on theory of machining and Coulomb friction caused on dry surface.

光導波形三軸触覚センサの感度特性向上に関する研究(知能機械,IIP2004 情報・知能・精密機器部門講演会)

Abstract An optical three-axis tactile sensor is comprised 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 a columnar feeler and conical feelers. Since the 2-by-2 conical feelers were detached from the acrylic board under too large horizontal force, the three-axis tactile sensor could detect friction coefficient of the object surface with limited range of shearing force only in the preceding authors' studies In the present paper, the authors proposed a new sensing element which has a columnar feeler and 8 conical feelers. The authors formulated a set of equations which could evaluate normal and shearing forces from integrated gray scale value and centroid displacement caused by conical feeler's contacts. To evaluate these sensing elements, we conducted a series of experiments using an x-z stage and a two-axis force sensor. It was found that relationship between centroid displacement and shearing force does not depend upon applied normal force, and that the present equations can estimate variations in normal force induced by increase of shearing force.

A Tactile Recognition System Mimicking Human Mechanism for Recognizing Surface Unevenness

A mathematical model was formulated on the basis of the results of psychophysical experiments in which human subjects discriminated fine steps on aluminum plates. The mathematical model emulated the real neuron discharge caused when a membrane potential exceeds a threshold. The membrane potential was determined by spatial and temporal summations of postsynaptic potential. To evaluate the mathematical model for surface texture recognition by robots, we performed a series of surface detection experiments using a robotic manipulator equipped with an optical three-axis tactile sensor. The single sensor cell of this sensor consisted of a columnar feeler and a 2-by-2 array of conical feelers. The three-axis force was calculated from the area-sum and area-difference of the conical feelers' contact areas. The robotic manipulator rubbed the tactile sensor on four brass plates with step-heights of 0, 0.05, 0.1 and 0.2 mm. It was found that the mathematical model could distinguish these step-heights.