A novel tactile sensor for robot applications

Eghtedari, F.; Morgan, Christopher L.

doi:10.1017/s0263574700006664

Cited by 13 publications

(5 citation statements)

References 4 publications

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“…The compliance matrix C is invertible (except for unusual geometries of strain measurement locations) so we find that f = C~le (21) From this, and Equation 5, we can approximate the normal load F z (x, y), and thus find total load acting normally on the plate as ¥ z (x,y)dxdy (22) Let the point at which the resultant force acts be denoted x. From basic statics, this is given as…”

Section: Inverse Solution Of the Proposed Plate Configurationmentioning

confidence: 99%

“…Consider a rod of length L, with mass per unit length p Al that is gripped above and below by two plate sensors; the free-body diagram is shown in Figure 4. From conditions of static equilibrium, we have (25) a,x Bl ) (26) Using the calculated values from equations (22) and (24), the values of p A and L, can be found. If the rod is gripped so that an overhang L 2 exists on the left of the diagram, the diagram and equations are simply reflected about the vertical axis, and readings from the second pair of sensors are used.…”

Section: Calculating Rod Length From Plate Sensor Datamentioning

confidence: 99%

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A tactile sensor based on thin-plate deformation

Ellis¹,

Ganeshan²,

Lederman³

1994

Robotica

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SUMMARYTraditionally, tactile sensors have been designed using compliant, rubber-like materials; when such a sensitized gripper grasps or otherwise manipulates an object, the normal strain deformation in the compliant material is sampled. The resulting information can be used to deduce simple local geometry of the contact, but the transduction process does not typically permit use of the individual strains in determining large-scale properties of the object (e.g., the inertia). Measurements of inertial parameters of grasped objects require accurate, low-hysteresis transduction that few tactile sensors currently provide.An alternative is to work from the task specification, and determine the tactile information that is necessary to accomplish the task. Here, we consider how to sense the length and mass of a uniform object that is gripped in a gravitational field, and show the design and assessment of a new kind of tactile sensor that is based on the theory of the deformation of thin plates. Features of this design include its potentially rugged realization, and its high-accuracy measurement that is more typical of force sensors than of tactile sensors.

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Section: Inverse Solution Of the Proposed Plate Configurationmentioning

confidence: 99%

Section: Calculating Rod Length From Plate Sensor Datamentioning

confidence: 99%

A tactile sensor based on thin-plate deformation

Ellis¹,

Ganeshan²,

Lederman³

1994

Robotica

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“…When integrated with a robot finger or multiple fingers, tactile sensing can be devised to measure grasped object profiles [1][2][3], identify object materials [4] and determine contacting load and location [5]. Some applications have been devised for controlling and manipulating grasped objects; for example, devices for detecting slip [6][7][8]. Brett and Stone [9] and Evans and Brett [10] examined an approach to determine a contact with soft objects and for adjusting a grasping strategy to control deformation.…”

Section: Introductionmentioning

confidence: 99%

Neural Network Training Techniques for Enhancing the Performance of a Distributive Tactile Sensor

Tongpadungrod

2013

International Journal of Advanced Robotic Systems

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This work describes neural network training techniques for enhancing the performance of a onedimensional beam for determining load positions. The system was a distributive system which relied on the detection of changes in the surface properties that can be seen across the surface. The demonstrated distributive system was 400 mm in length. The applied load positions within the range 60 -300 mm could be determined with an average percentage error of 0.2% of the beam length which corresponded to a position error of 0.8 mm using a network trained with 10 training positions. It was found that the errors were higher for the load applied near the edges of the beam, leading to an average percentage error of 3.6% for the whole length of the beam. The normalization of the network output can be employed to reduce the average percentage error by approximately 1% for a given number of training positions. The performance was improved by introducing more training positions in the less sensitive area. The described training technique not only reduced the prediction error but also enlarged the areas where the prediction errors were satisfactorily small. Using the described technique, the overall prediction error could be decreased by 0.13 -0.24% of the beam length for 30 -10 training positions.The area where the prediction errors were within 2 mm was increased by 14.5 -7.3% of the beam length for a network trained with 4 training positions in the middle portion using 10 -30 training positions.

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“…In a slight deviation from the conventional approaches, Kyberd and Chappell [9] have developed a slip sensor based on forced oscillations, which detects the sound produced by vibrations using a microphone. Eghtedari and Morgan [10] have used photoelastic material and a solidstate camera with a detailed processing to infer the object slip. With the rapid development of VLSI chip fabrication technology many slip sensors have been designed as sensing arrays.…”

Section: Introductionmentioning

confidence: 99%

A dynamic tactile sensor on photoelastic effect

Dubey

Crowder

2006

Sensors and Actuators A: Physical

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Certain photoelastic materials exhibit birefringent characteristics at a very low level of strain. This property of material may be suitable for dynamic or wave propagation studies, which can be exploited for designing tactile sensors. This paper presents the design, construction and testing of a novel dynamic sensor based on photoelastic effect, which is capable of detecting object slip as well as providing normal force information. The paper investigates the mechanics of object slip, and develops an approximate model of the sensor. This allows visualization of various parameters involved in the sensor design. The model also explains design improvements necessary to obtain continuous signal during object slip. The developed sensor has been compared with other existing sensors and experimental results from the sensor have been discussed. The sensor is calibrated for normal force which is in addition to the dynamic signal that it provides from the same contact location. The sensor has a simple design and is of a small size allowing it to be incorporated into robotic fingers, and it provides output signals which are largely unaffected by external disturbances.

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A novel tactile sensor for robot applications

Cited by 13 publications

References 4 publications

A tactile sensor based on thin-plate deformation

A tactile sensor based on thin-plate deformation

Neural Network Training Techniques for Enhancing the Performance of a Distributive Tactile Sensor

A dynamic tactile sensor on photoelastic effect

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