Improved GelSight Tactile Sensor for Measuring Geometry and Slip

A GelSight sensor uses an elastomeric slab covered with a reflective membrane to measure tactile signals. It measures the 3D geometry and contact force information with high spacial resolution, and successfully helped many challenging robot tasks. A previous sensor, based on a semi-specular membrane, produces high resolution but with limited geometry accuracy. In this paper, we describe a new design of GelSight for robot gripper, using a Lambertian membrane and new illumination system, which gives greatly improved geometric accuracy while retaining the compact size. We demonstrate its use in measuring surface normals and reconstructing height maps using photometric stereo. We also use it for the task of slip detection, using a combination of information about relative motions on the membrane surface and the shear distortions. Using a robotic arm and a set of 37 everyday objects with varied properties, we find that the sensor can detect translational and rotational slip in general cases, and can be used to improve the stability of the grasp.Comment: IEEE/RSJ International Conference on Intelligent Robots and System

Biomechanical Texture Coding and Transmission of Texture Information in Rat Whiskers

Classically, texture discrimination has been thought to be based on ‘global’ codes, i.e. frequency (signal analysis based on Fourier analysis) or intensity (signal analysis based on averaging), which both rely on integration of the vibrotactile signal across time and/or space. Recently, a novel ‘local’ coding scheme based on the waveform of frictional movements, discrete short- lasting kinematic events (i.e. stick-slip movements called slips) has been formulated. In the first part of my study I performed biomechanical measurements of relative movements of a rat vibrissa across sandpapers of different roughness. My major finding is that the classic global codes convey some information about texture identity but are consistently outperformed by the slip-based local code. Moreover, the slip code also surpasses the global ones in coding for active scanning parameters. This is remarkable as it suggests that the slip code would explicitly allow the whisking rat to optimize perception by selecting goal-specific scanning strategies. I therefore provide evidence that short stick-slip events may contribute to the perceptual mechanism by which rodent vibrissa code surface roughness. In the second part, I studied the biomechanics of how such events are transmitted from tip to follicle where mechano-transduction occurs. For this purpose, ultra-fast videography recording of the entire beam of a plucked rat whisker rubbing across sandpaper was employed. I found that slip events are conveyed almost instantly from tip to follicle while amplifying moments by a factor of about 1000. From these results, I argue that the mechanics of the whisker serve as a passive amplification device that faithfully represents stick-slip events to the neuronal receptors. Using measures of correlation, I moreover found that amongst the kinematic 8 variables, acceleration portrays dynamic variables (forces) best. The time series of acceleration at the base of the whisker provided a fair proxy to the time series of forces (dynamical variables) acting on the whisker base. Acceleration measurements (easily done via videography) may therefore provide an access to at least the relative amplitude of forces. This may be important for future work in behaving animals, where dynamical variables are notoriously difficult to measure

Hierarchical tactile sensation integration from prosthetic fingertips enables multi-texture surface recognition\u3csup\u3e†\u3c/sup\u3e

Multifunctional flexible tactile sensors could be useful to improve the control of prosthetic hands. To that end, highly stretchable liquid metal tactile sensors (LMS) were designed, manufactured via photolithography, and incorporated into the fingertips of a prosthetic hand. Three novel contributions were made with the LMS. First, individual fingertips were used to distinguish between different speeds of sliding contact with different surfaces. Second, differences in surface textures were reliably detected during sliding contact. Third, the capacity for hierarchical tactile sensor integration was demonstrated by using four LMS signals simultaneously to distinguish between ten complex multi-textured surfaces. Four different machine learning algorithms were compared for their successful classification capabilities: K-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and neural network (NN). The time-frequency features of the LMSs were extracted to train and test the machine learning algorithms. The NN generally performed the best at the speed and texture detection with a single finger and had a 99.2 ± 0.8% accuracy to distinguish between ten different multi-textured surfaces using four LMSs from four fingers simultaneously. The capability for hierarchical multi-finger tactile sensation integration could be useful to provide a higher level of intelligence for artificial hands

Tactile on-chip pre-processing with techniques from artificial retinas

The interest in tactile sensors is increasing as their use in complex unstructured environments is demanded, like in tele-presence, minimal invasive surgery, robotics etc. The matrix of pressure data these devices provide can be managed with many image processing algorithms to extract the required information. However, as in the case of vision chips or artificial retinas, problems arise when the array size and the computation complexity increase. Having a look to the skin, the information collected by every mechanoreceptor is not carried to the brain for its processing, but some complex pre-processing is performed to fit the limited throughput of the nervous system. This is specially important for high bandwidth demanding tasks. Experimental works report that neural response of skin mechanoreceptors encodes the change in local shape from an offset level rather than the absolute force or pressure distributions. This is also the behavior of the retina, which implements a spatio-temporal averaging. We propose the same strategy in tactile preprocessing, and we show preliminary results when it faces the detection of the slip, which involves fast real-time processing.Ministerio de Ciencia y Tecnología TIC2003 - 09817-C0

Integrated Circuitry to Detect Slippage Inspired by Human Skin and Artificial Retinas

This paper presents a bioinspired integrated tactile coprocessor that is able to generate a warning in the case of slippage via the data provided by a tactile sensor. Some implementations use different layers of piezoresistive and piezoelectric materials to build upon the raw sensor and obtain the static (pressure) as well as the dynamic (slippage) information. In this paper, a simple raw sensor is used, and a circuitry is implemented, which is able to extract the dynamic information from a single piezoresistive layer. The circuitry was inspired by structures found in human skin and retina, as they are biological systems made up of a dense network of receptors. It is largely based on an artificial retina , which is able to detect motion by using relatively simple spatial temporal dynamics. The circuitry was adapted to respond in the bandwidth of microvibrations produced by early slippage, resembling human skin. Experimental measurements from a chip implemented in a 0.35-mum four-metal two-poly standard CMOS process are presented to show both the performance of the building blocks included in each processing node and the operation of the whole system as a detector of early slippage.Ministerio de Economía y Competitividad TEC2006-12376-C02-01Gobierno de España TEC2006- 1572

Characterizing and imaging gross and real finger contacts under dynamic loading

We describe an instrument intended to study finger contacts under tangential dynamic loading. This type of loading is relevant to the natural conditions when touch is used to discriminate and identify the properties of the surfaces of objects — it is also crucial during object manipulation. The system comprises a high performance tribometer able to accurately record in vivo the components of the interfacial forces when a finger interacts with arbitrary surfaces which is combined with a high-speed, high-definition imaging apparatus. Broadband skin excitation reproducing the dynamic contact loads previously identified can be effected while imaging the contact through a transparent window, thus closely approximating the condition when the skin interacts with a non-transparent surface during sliding. As a preliminary example of the type of phenomenon that can be identified with this apparatus, we show that traction in the range from 10 to 1000 Hz tends to decrease faster with excitation frequency for dry fingers than for moist fingers

Relaying the High-Frequency Contents of Tactile Feedback to Robotic Prosthesis Users: Design, Filtering, Implementation, and Validation

It is known that high-frequency tactile information conveys useful cues to discriminate important contact properties for manipulation, such as first contact and roughness. Despite this, no practical system, implementing a modality matching paradigm, has been developed so far to convey this information to users of upper-limb prostheses. The main obstacle to this implementation is the presence of unwanted vibrations generated by the artificial limb mechanics, which are not related to any haptic exploration task. In this letter, we describe the design of a digital system that can record accelerations from the fingers of an artificial hand and reproduce them on the user's skin through voice-coil actuators. Particular attention has been devoted to the design of the filter, needed to cancel all those vibrations measured by the sensors that do not convey information on meaningful contact events. The performance of the newly designed filter is also compared with the state of the art. Exploratory experiments with prosthesis users have identified some applications where this kind of feedback could lead to sensory-motor performance enhancement. Results show that the proposed system improves the perception of object-salient features such as first-contact events, roughness, and shape