Slippage degree estimation for dexterous handling of vision-based tactile sensor

Ito, Yuji; Kim, YoungWoo; Obinata, Goro

doi:10.1109/icsens.2009.5398268

Cited by 15 publications

(12 citation statements)

References 4 publications

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“…In the proposed method, the reference image is frequently updated to reflect a recent deformation of the stick region [37]. By properly updating the reference image, we can estimate the deformation of the stick region and the dot displacement between the reference and current images in an accurate manner.…”

Section: B Proposed Methods For Estimating the Stick Ratiomentioning

confidence: 99%

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

2011

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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 [1], 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.

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Section: B Proposed Methods For Estimating the Stick Ratiomentioning

confidence: 99%

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

2011

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“…These approaches have been shown to be able to estimate the magnitude of slip and, in the case of [25], are able to estimate a safety margin of grasping forces before slip takes place. A number of parameters must be set before direct sensing of object motion can be used as a viable slip detection method and periods of experimentation and off-line calibration may be needed.…”

Section: B Slip Detection Working Principlesmentioning

confidence: 97%

“…Approaches based on the direct sensing of object motion have also been proposed (for example, [23], [24], and [25]). These approaches have been shown to be able to estimate the magnitude of slip and, in the case of [25], are able to estimate a safety margin of grasping forces before slip takes place.…”

Section: B Slip Detection Working Principlesmentioning

confidence: 98%

A Slip Detection and Correction Strategy for Precision Robot Grasping

Stachowsky

Hummel

Moussa

et al. 2016

IEEE/ASME Trans. Mechatron.

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This paper presents a grasp force regulation strategy for precision grasps. The strategy makes no assumptions about object properties and surface characteristics and can be used with a wide range of grippers. It has two components: a slip signal detector that computes the magnitude of slip and a grasping force set point generator that acts on the detector's output. The force set point generator is designed to ensure that slip is eliminated without using excessive force. This is particularly important in several situations like grasping fragile objects or in-hand manipulation of thin small objects. Several experiments were conducted to simulate various grasping scenarios with different objects. Results show that the strategy was very successful in dealing with uncertainty in object mass, surface characteristics, or rigidity. The strategy is also insensitive to robot motion.

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“…In this experimental setup, and was 53 mm and 1.3326. When the flat object is in contact with the touchpad, we obtained the depth at from the side camera and calculated the depth at from (27) to determine the constant parameters and (28) and (29). We obtained and in (27) by the least-square method, changing in (29) from 1 pixel to 90 pixel.…”

Section: A Calibration and Establishing Ground Truthmentioning

confidence: 99%

“…6(b). We define to represent the angular difference between the initial state and the current state as follows: (29) where is the constant parameter. We calculate the integral of (29) numerically by using at each pixel of the image (the size of the pixel is 0.08 0.08 mm).…”

Section: Compensation For Membrane Deformationmentioning

confidence: 99%

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

Ito

Kim

Nagai

et al. 2012

IEEE Trans. Automat. Sci. Eng.

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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.Note to Practitioners-More reliable and sensitive skin of robot hands is realized by shape-sensing of objects in contact. With the shape-sensing, we can achieve a stable grip of robot hands avoiding protruding portion, and obtain reliable grip positions. With shape-deformation of flexible objects, we can avoid the grasped object (with robot fingers) by controlling the grasping force. Although various types of tactile sensors for robot hands have been developed, there have been few sensors that shape-sense of objects in contact. This paper suggests a three-dimensional shape-sensing method of object in contact. The sensor can be compact in size and structure, since we use only a single camera. Although we used many parameters, the proposed method allows the practitioners to implement the proposed method in an easy manner to their applications. We should evaluate how efficient the proposed method is for various applications. Future work includes implementation to the robot hands.

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Slippage degree estimation for dexterous handling of vision-based tactile sensor

Cited by 15 publications

References 4 publications

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

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

A Slip Detection and Correction Strategy for Precision Robot Grasping

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

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