In this paper, we propose an artificial neural network fitting model to estimate contact position an image-based areal touch sensor(IATS) with soft physical contact. First, the principle of the proposed artificial neural network fitting model for contact position estimation is described. Then, the structure of the IATS for verifying the algorithm is described. Second, an experiment was conducted to verify the model. Experimental data was obtained and analyzed for accuracy. Accuracy is estimated based on the relative error rate to show the accuracy between actual and estimated contact positions. As a result, the accuracy for each axis is as follows. The accuracy for the X-axis is 86.7% on average and the accuracy for the Y-axis is 96.5% on average. The depth accuracy is 94.9%. It is analyzed to solve various problems and it is expected that it will be possible to develop a sensor with accuracy similar to the actual contact position in the future.

/pdf/contact-position-estimation-algorithm-using-image-based-1dz3mz82rs.pdf

Contact Position Estimation Algorithm using Image-based Areal Touch Sensor based on Artificial Neural Network Prediction

Flexible tactile sensors can provide valuable feedback to intelligent robots regarding the environment around them This is especially important when robots such as, service robots share a workspace with humans This paper presents a contact force measurement algorithm of a flexible tactile sensor This sensor is manufactured by a direct-writing technique, which is one 3D printing method, using multi-walled carbon nano-tubes An analog signal processing circuit has been designed and implemented to reduce noise contained in the sensor output In addition, a digital version of the Butterworth filter was implemented by software running on a microcontroller Through various experiments, characteristics of the sensor system have been identified Based on three traits, an algorithm to detect the contact and measure the contact force has been developed The entire system showed a promising prospect to detect the contact over a large and curved area

Development of Contact Force Measurement Algorithm for a 3D Printing-type Flexible Tactile Sensor

A study on capacitive characteristics of stylus pen for touch panel are progressed in this paper. Also the main factors for capacitive sensitivity are studied. Namely, highly sensitive stylus pen which can be applied to capacitive touch panel are studied based on the analysis of materials and process conditions regardless of pattern shapes. Stylus pen was made of PDMS(Poly-Di-Methyl-Siloxane) and conductive metal powders which does not damage the touch panel surface. We tried to get the advantages of both the properties of soft PDMS and conductive metal powders. We found that potential difference of capacitance change with conductivity of the composite materials(PDMS + metal powders) it implies that during touch process, large voltage difference can be caused by the high conductive materials of stylus pen. Stylus pen made by PDMS with mixed with Ag powders which has large conductivity shows more capacitance change of 1 pF than PDMS with other materials of Ni or C powders.

/pdf/a-study-on-capacitance-properties-of-stylus-pen-applied-to-25ksbgfsud.pdf

A Study on Capacitance Properties of Stylus Pen Applied to Capacitive Touch Panel

In this study, we propose an optimal design and new fabrication method for a slim tactile sensor Slim tactile sensor can detect 3-axial forces and has suitable flexibility for intelligent robot fingers To amplify the contact signal, a unique table-shaped structure was attempted A new layer-by-layer fabrication process for polymer micromachining that can make a 3D structure by using a sacrificial layer was proposed A table-shaped epoxy sensing plate with four legs was built on top of a flexible polymer substrate The plate can convert an applied force to a concentrated stress Normal and shear forces can be detected by combining responses from metal strain gauges embedded in the polymer substrate The optimal positions of the strain gauges are determined using the strain distribution obtained from finite element analysis

/pdf/polymer-based-slim-tactile-sensor-optimal-design-and-new-1c5x3o7o4n.pdf

Jeong-Il Lee

Papers

Polymer Based Slim Tactile Sensor: Optimal Design and New Fabrication Method