Vision-based Tactile Sensor Research Articles

Vision‐based tactile sensor using depth from defocus for artificial finger in hand prosthesis

A vision-based tactile sensor has been implemented to build an artificial fingers capable of grasping for the hand prosthesis. The tactile sensor hardware is composed of an elastomer sensing part with one layer of markers and an image sensor. By employing the depth from defocus technique, three-dimensional contact force distribution can be reconstructed from the 2D images of only one layer of markers. The proposed hardware and algorithm have been validated through experiments.

Measurement of Multi-axis Contact Force by Vision-based Tactile Sensor Using Elastic Membrane

Measurement of Multi-axis Contact Force by Vision-based Tactile Sensor Using Elastic Membrane

Acquisition of Contact Force and Slippage Using a Vision-Based Tactile Sensor with a Fluid-Type Touchpad for the Dexterous Handling of Robots

This paper presents a new approach for estimating contact force and slippage by using a vision-based tactile sensor with a fluid-type touchpad for the dexterous handling of robots. The sensor consists of a CCD camera, LED lights, a transparent acrylic plate and a deformable touchpad. The sensor can obtain a variety of tactile information, such as the contact force, shape, contact region, position and orientation of an object in contact with the fluid-type touchpad. The previous method for measuring contact force requires extensive calculation; this paper proposes a new method based on lookup tables for measuring normal force, tangential force and moment, using a fluid-type touchpad. Additionally, we clarify the mechanism of slippage between a fluid-type touchpad and a contacted object. This mechanism is efficient for applying the proposed slippage estimation method to a fluid-type touchpad. The validation of the proposed methods is confirmed in the experimental results.

Vision-Based Tactile Sensing and Shape Estimation Using a Fluid-Type Touchpad

In this paper, we propose a new method to estimate the shape and irregularity of objects by a vision-based tactile sensor, which consists of a CCD camera, LED lights, transparent acrylic plate, and a touchpad which consists of an elastic membrane filled with translucent red water. Intensities of red, green and blue bands of the traveling light in the touchpad are analyzed in this study to estimate the shape/irregularity of the object. The LED light traveling in the touchpad is scattered and absorbed by the red pigment in the fluid. The depth of the touchpad is estimated by using the intensity of the light obtained from the red-green-blue (RGB) values of the image, in consideration of the scattering and reflection effects. The reflection coefficient that depends on the shape of the membrane, was decoupled in the proposed formulation. The intensity of the traveling light is represented with the geometrical parameters of the touchpad surface. In order to reduce the approximation error caused by unmodeled factors, we compensate the error by using a function of the deformation of the membrane. The validation of the proposed method is confirmed through experimental results.

Robust Slippage Degree Estimation Based on Reference Update of Vision-Based Tactile Sensor

In this paper, we propose a new slippage degree estimation method of a vision-based tactile sensor. The advantage of the vision-based tactile sensor is simultaneous acquisition of the slippage degree, a multidimensional force and a moment. A CCD camera captures the sensor surface which has regularly arrayed dots. The slippage degree on the sensor surface is determined by the stick ratio obtained from the displacements of dots in the captured images. In our previous work , the stick ratio was successfully applied to avoid slippage or the shape deformation of grasped objects. Based on the adaptive selection of the reference image and the compensation of the dot displacement, the proposed method in this study extends use of the previously developed algorithm, to dynamically complex but general situations as follows. First, the contact surface deforms after the macroscopic slippage or the slippage direction is changed. Second, the contact surface rotates with an applied moment. Third, the captured image is locally zoomed with a significant change of a grip force. A heuristic weighted average method is also proposed to decrease each dot's variation in the captured image. Usefulness of the proposed method is confirmed through experimental results.

Contact State Estimation by Vision-Based Tactile Sensors for Dexterous Manipulation with Robot Hands Based on Shape-Sensing

We propose a new method for estimating the contact state of objects with varying shapes on a vision-based fluid-type tactile sensor, which touch pad is an elastic transparent membrane of silicon rubber with dotted pattern printed on its inner side. The membrane is filled with translucent red colored water. The proposed method leads to better understanding of the object's shape and movement, and can be applied for accomplishing reliable and dexterous handling tasks by robot hands.

Slippage Degree Estimation by Using Vision-Based Tactile Sensor for Dexterous Handling

In this paper, we present a new slippage degree estimation method, where the vision-based tactile sensor is used to measure multi-dimensional force and moment in contact with an object. We proposed a new method to obtain the stick ratio based on a quantization process of the maximum displacement in the stick region. The stick ratio is useful when we detect macroscopic slippage in advance. We show that the proposed method can be applied to wider situations and obtain more accurate estimation of stick ratio than the previous method. We can use the proposed method for the following situations. First, the applied normal force seriously changes or a certain amount of moment applies to the contact surface. Second, a macroscopic slippage occurs and the sensor surface re-establishs the contact. Third, a complex history of contact makes each local behavior of the surface difficult. The image processing method has been proposed to decrease the data variation of the captured CCD camera image and to cope with the wider situations of contact conditions. The usefulness of the proposed method is confirmed through the experimental results.

B202 画像処理を用いた触覚センサによる視触覚融合システム(B2-1 福祉工学1)

B202 画像処理を用いた触覚センサによる視触覚融合システム(B2-1 福祉工学1)

C202 画像処理を用いた内視鏡用触覚センサの試作(C2-1 手術・治療支援デバイス1)

C202 画像処理を用いた内視鏡用触覚センサの試作(C2-1 手術・治療支援デバイス1)

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