Pilot Study: Low Cost GelSight Sensor

GelSight sensor and related technology have been studied a decade to the date. It was proven that it is worth to explore in many haptics and tactile sensing applications. Elastomer, reflective coating, lighting, and camera were the main challenges of making a GelSight sensor within a short period. In this workshop paper, we present our preliminary studies on how to make a GelSight sensor using low cost material. In this study, we used a clear silicone cosmetic sponge as the elastomeric slab and that skipped the degassing process and hours of curing time in making it. Moreover, we used Psycho Paint® for the reflective coating, Light Emitting Diodes (LEDs) for the lighting, and Logitech C270 webcam for our experimental setup. Furthermore, in this study Ultraviolet (UV) ink and UV LEDs have been tested as a marker for the reflective coating and lighting respectively. UV ink markers are invisible using ordinary LED but can be made visible using UV lighting. Comparable results have been found to show the effectiveness of our setup

Low-cost GelSight with UV Markings: Feature Extraction of Objects Using AlexNet and Optical Flow without 3D Image Reconstruction

GelSight sensor has been used to study microgeometry of objects since 2009 in tactile sensing applications. Elastomer, reflective coating, lighting, and camera were the main challenges of making a GelSight sensor within a short period. The recent addition of permanent markers to the GelSight was a new era in shear/slip studies. In our previous studies, we introduced Ultraviolet (UV) ink and UV LEDs as a new form of marker and lighting respectively. UV ink markers are invisible using ordinary LED but can be made visible using UV LED. Currently, recognition of objects or surface textures using GelSight sensor is done using fusion of camera-only images and GelSight captured images with permanent markings. Those images are fed to Convolutional Neural Networks (CNN) to classify objects. However, our novel approach in using low-cost GelSight sensor with UV markings, the 3D height map to 2D image conversion, and the additional non-Gelsight captured images for training the CNN can be eliminated. AlexNet and optical flow algorithm have been used for feature recognition of five coins without UV markings and shear/slip of the coin in GelSight with UV markings respectively. Our results on confusion matrix show that, on average coin recognition can reach 93.4% without UV markings using AlexNet. Therefore, our novel method of using GelSight with UV markings would be useful to recognize full/partial object, shear/slip, and force applied to the objects without any 3D image reconstruction

Camera-based force and tactile sensor

© Springer International Publishing AG, part of Springer Nature 2018. Tactile information has become a topic of great interest in the design of devices that explore the physical interaction with the external environment. For instance, it is important for a robot hand to perform manipulation tasks, such as grasping and active touching, using tactile sensors mounted on the finger pad to provide feedback information. In this research we present a novel device that obtains both force and tactile information in a single integrated elastomer. The proposed elastomer consists of two parts, one of which is transparent and is wrapped in another translucent one that has eight conical sensing elements underneath. Two parts are merged together via a mould. A CCD camera is mounted at the bottom of the device to record the images of two elastomer mediums illuminated by the LED arrays set inside of the device. The method consists of evaluating the state of the contact surface based on analysis of the image of two elastomers. The external deformation of the elastomer is used to measure three force components Fz, Mx and My. The measurement is based on the area changes of the conical sensing elements under different loads, while the image of the inner transparent elastomer captures the surface pattern, which can used to obtain tactile information