Fingerprint-enhanced capacitive-piezoelectric flexible sensing skin to discriminate static and dynamic tactile stimuli

nspired by the structure and functions of the human skin, a highly sensitive capacitive‐piezoelectric flexible sensing skin with fingerprint‐like patterns to detect and discriminate between spatiotemporal tactile stimuli including static and dynamic pressures and textures is presented. The capacitive‐piezoelectric tandem sensing structure is embedded in the phalange of a 3D‐printed robotic hand, and a tempotron classifier system is used for tactile exploration. The dynamic tactile sensor, interfaced with an extended gate configuration to a common source metal oxide semiconductor field effect transistor (MOSFET), exhibits a sensitivity of 2.28 kPa−1. The capacitive sensing structure has nonlinear characteristics with sensitivity varying from 0.25 kPa−1 in the low‐pressure range (<100 Pa) to 0.002 kPa−1 in high pressure (≈2.5 kPa). The output from the presented sensor under a closed‐loop tactile scan, carried out with an industrial robotic arm, is used as latency‐coded spike trains in a spiking neural network (SNN) tempotron classifier system. With the capability of performing a real‐time binary naturalistic texture classification with a maximum accuracy of 99.45%, the presented bioinspired skin finds applications in robotics, prosthesis, wearable sensors, and medical devices

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

Development of an intelligent object for grasp and manipulation research

Kõiva R, Haschke R, Ritter H. Development of an intelligent object for grasp and manipulation research. Presented at the ICAR 2011, Tallinn, Estonia.In this paper we introduce a novel device, called iObject, which is equipped with tactile and motion tracking sensors that allow for the evaluation of human and robot grasping and manipulation actions. Contact location and contact force, object acceleration in space (6D) and orientation relative to the earth (3D magnetometer) are measured and transmitted wirelessly over a Bluetooth connection. By allowing human-human, human-robot and robot-robot comparisons to be made, iObject is a versatile tool for studying manual interaction. To demonstrate the efficiency and flexibility of iObject for the study of bimanual interactions, we report on a physiological experiment and evaluate the main parameters of the considered dual-handed manipulation task

Tele-operated high speed anthropomorphic dextrous hands with object shape and texture identification

This paper reports on the development of two number of robotic hands have been developed which focus on tele-operated high speed anthropomorphic dextrous robotic hands. The aim of developing these hands was to achieve a system that seamlessly interfaced between humans and robots. To provide sensory feedback, to a remote operator tactile sensors were developed to be mounted on the robotic hands. Two systems were developed, the first, being a skin sensor capable of shape reconstruction placed on the palm of the hand to feed back the shape of objects grasped and the second is a highly sensitive tactile array for surface texture identification

Tactile sensing chips with POSFET array and integrated interface electronics

This work presents the advanced version of novel POSFET (Piezoelectric Oxide Semiconductor Field Effect Transistor) devices based tactile sensing chip. The new version of the tactile sensing chip presented here comprises of a 4 x 4 array of POSFET touch sensing devices and integrated interface electronics (i.e. multiplexers, high compliance current sinks and voltage output buffers). The chip also includes four temperature diodes for the measurement of contact temperature. Various components on the chip have been characterized systematically and the overall operation of the tactile sensing system has been evaluated. With new design the POSFET devices have improved performance (i.e. linear response in the dynamic contact forces range of 0.01–3N and sensitivity (without amplification) of 102.4 mV/N), which is more than twice the performance of their previous implementations. The integrated interface electronics result in reduced interconnections which otherwise would be needed to connect the POSFET array with off-chip interface electronic circuitry. This research paves the way for CMOS (Complementary Metal Oxide Semiconductor) implementation of full on-chip tactile sensing systems based on POSFETs