Design of a New Robot Skin

The automated robots utilizing the traditional rigid tactile sensors have achieved significant success in effective task execution. Advancing into the era of service robots and humanoids that should perform sophisticated works in daily life, recent research trends in robotic tactile sensors have been shifting from the conventional rigid sensors to flexible/stretchable sensors. Over the past decade, the flexible/stretchable tactile sensors with human skin‐like mechanical compliance and stimulation perceptions have seen considerable advances. However, there are many substantial remaining challenges to produce practically useful flexible/stretchable tactile sensors such as the signal hysteresis originating from sensor material and the limited spatial resolution resulting from excessive addressing lines and signal interferences. Incorporation of learning‐based algorithms and data analysis techniques have been introduced recently and made remarkable successes in improving the challenges. Because most robotic tactile sensors are fabricated using the electronic sensing mechanisms or platforms, this article presents a concise overview on recent flexible/stretchable tactile sensors. This article introduces a brief discussion on the sensor performance parameters and sensing mechanisms, and the algorithmic approaches. In addition, it addresses existing challenges associated with current tactile array sensors and algorithms, then discusses prospects, and proposes a research direction for immediate practical uses in robots.

Femtosecond laser micro-fabricated flexible sensor arrays for simultaneous mechanical and thermal stimuli detection

In this paper tactile proximity sensors for close human-robot interactions based on a previously developed sensor are introduced. Using the same sensing technology, we developed large area tactile proximity sensors as a robot skin and small sensors which we have integrated in an anthropomorphic robot hand. Tactile sensing in the area of robotics for close human-interaction is still a challenging task. In the most cases tactile sensors need to be supported by other sensor modalities to perceive the robots environment before contacts occur. To overcome this issue we developed tactile proximity sensors for robot surfaces and for robot grippers. Both sensors, their behaviour and a model of the tactile sensor will be discussed in this paper.

With the advent of the aging society, the demand for nursing care for the elderly is becoming much larger. The application of robotics to helping on-site caregivers is consequently one of the most important new areas of robotics research. Such humaninteractive robots, which share humans’ environments and interact with them, should be covered with soft areal tactile sensors for safety, communication, and dextrous manipulation. Tactile sensors have interested many researchers and various types of tactile sensors have been proposed so far. Many tactile sensors have been developed on the basis of microelectro-mechanical system (MEMS) technology (for example, (Suzuki, 1993; Souza & Wise, 1997)). They have a high-density and narrow covering area realized by applying MEMS technology, and as a result, are not suitable for covering a large area of a robot’s surface. Some tactile sensors suitable for use on robot fingers or grippers have also been developed (Nakamura & Shinoda, 2001; Yamada et al., 2002; Shimojo et al., 2004). Many of them have the ability to detect tangential stress and can be used in grasping force control. Their main target is robot fingers, and consequently they were not designed to cover a large area. There are also commercially available tactile sensors such as those offered by Tekscan (Tekscan, 2008) based on pressure-sensitive ink or rubber, and KINOTEXTM tactile sensors (Reimer & Danisch, 1999) utilizing the change in the intensity of light scattered by the covering urethane foam when deformed. However, they are not sufficiently accurate because of strong hysteresis and creep characteristics. The idea of covering a large area of a robot’s surface with soft tactile skinlike sensors is attracting researchers (Lumelsky et al., 2001). Some human-interactive robots for which a large area of their surface is covered with soft tactile sensors have actually been developed (Inaba et al. 1996; Tajima et al. 2002; Kanda et al. 2002; Mitsunaga et al. 2006; Ohmura et al., 2006; Ohmura & Kuniyoshi, 2007). However, the tactile sensors are not suitable for humaninteractive robots, particularly when physical labor using tactile sensation is required. For example, one tactile sensor in (Tajima et al. 2002) has only 3 values as its output, and another tactile sensor in (Tajima et al. 2002) is gel-type and cannot be used over a long period because of the evaporation of the contained water. The tactile sensor in (Mitsunaga et al. 2006) has only 56 elements in total. Flexible fabric-based tactile sensors using an electrically conductive fabric have also been proposed for covering a robot (Inaba et al. 1996), but the O pe n A cc es s D at ab as e w w w .in te ch w eb .o rg

Tactile pressure sensors are flexible, thin sheets containing a matrix of sensors, which are used to measure earth pressures in geotechnical applications. Although more successful in static and 1-g shaking table tests, available tactile sensors do not capture the full amplitude content of dynamic signals in centrifuge experiments. This is due to under-sampling and the sensor’s frequency-dependent response. A minimum sampling rate of 3000 samples per second is recommended in centrifuge testing to avoid under-sampling and capture frequencies up to 300 Hz in model scale. A new dynamic calibration methodology is proposed to characterize the sensor’s frequency-dependent response by evaluating how it attenuates pressure at higher frequencies. Sinusoidal loads are applied to the sensor at different frequencies, and the applied pressure is simultaneously recorded by a reference load cell and a tactile sensor. A transfer function is then calculated by dividing the Fourier pressure amplitude of the load cell by that of the tactile sensor at a given frequency. To dynamically calibrate tactile sensors, this transfer function may be used as an amplitude correction function under general loading. Through a series of blind dynamic tests, the proposed frequency-dependent, dynamic calibration methodology is shown to reduce the peak residuals between the tactile and reference sensor recordings from approximately 0.55 to 0.15 at frequencies below 300 Hz.

This paper introduces a novel tactile sensor with the ability to detect objects in the sensor's near proximity. For both tasks, the same capacitive sensing principle is used. The tactile part of the sensor provides a tactile sensor array enabling the sensor to gather pressure profiles of the mechanical contact area. Several tactile sensors have been developed in the past. These sensors lack the capability of detecting objects in their near proximity before a mechanical contact occurs. Therefore, we developed a tactile proximity sensor, which is able to measure the current flowing out of or even into the sensor. Measuring these currents and the exciting voltage makes a calculation of the capacitance coupled to the sensor's surface and, using more sensors of this type, the change of capacitance between the sensors possible. The sensor's mechanical design, the analog/digital signal processing and the hardware efficient demodulator structure, implemented on a FPGA, will be discussed in detail.

This article presents a novel robot skin that integrates both proximity and tactile sensors in a nursing robot to maximize the safety of patient transfer tasks. Two types of sensors are mounted on a honeycomb substrate made of flexible photosensitive resin. The proximity sensor consists of several distance sensor arrays, each with 16 laser sensors connected to a microprocessor via an inter-integrated circuit bus. The sensor array is made of a flexible printed circuit, and the distance between the robotic arm and object is measured based on the time-of-flight principle. The tactile sensor consists of multiple 125 mm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times125$ </tex-math></inline-formula> mm pressure sensor patches, each integrating 64 piezoresistive pressure sensors. This article presents the design and manufacture of the sensitive skin and proposes the safety control strategies of a nursing robotic arm using sensor information. In particular, by employing proximity sensors to detect approaching objects, the robotic arm can avoid high-speed collisions. The posture of the arm can be adjusted by using the tactile sensors to prevent the patient from slipping off and failure of the robotic arm. Preliminary experiments were conducted using the proposed sensitive skin and our nursing robot. The results are presented to demonstrate the accuracy of the sensor data and feasibility of the safety control strategies.

Since tactile perception and robotic manipulation play important roles in human survival, we propose a new method for developing robotic tactile sensors based on the structural colours of Morpho menelaus (a kind of Morpho butterfly). The first task is to fabricate a flexible bioinspired grating with a similar microstructure to the wings of Morpho menelaus using the transfer technique, onto the surfaces of polydimethylsiloxane (PDMS) films. The second task, depending on the angle of diffracted light, is to integrate the flexible diffraction grating with a polychromatic light source and a CCD camera, and then predict the position and magnitude of the contact force caused by a change in the diffraction pattern. The final task is to set up an experimental calibration platform and a marker point array with an interval of 1 mm for an image processing algorithm and a deep learning method to establish the relationship between the contact point position, and the magnitude of the force and diffraction pattern. The results showed that this tactile sensor has high sensitivity and resolution, with the position of the contact force of 1 mm. This practical application of the UR-5 manipulator verifies the feasibility of the prototype as a tactile sensor. This tactile sensing method may be widely used in robotics by miniaturising the design.

Tactile sensing technology has made significant progress towards the development of devices where robot fingers must have the ability of multi-dimensional tactile sensing in order to perform grasping and manipulating tasks (Chi & Shida, 2004); (Webster, 1998); (Nicholls & Lee, 1989); (Tarchanidis & Lygouras, 2001); (Da Silva et al., 2000). Therefore, many researchers have tried to develop various types of tactile sensors by applying MEMS technologies which usually rely on the measurement of pressure or force on a sensing element (Hasegawa et al, 2007). A variety of different types of sensors have been used, including resistive strain gauges, piezoelectric film, infrared displacement sensors, capacitive sensors, sensors detecting conductance, magnetic, magnetoelectric and ultrasonic sensors. Frequently large numbers of sensing elements are built into an array and the outputs of those sensors are processed, often in conjunction with a mathematical model, to give an assessment of the contacting object. Nowadays, force sensing becomes an important component for diver applications in biomedical applications and orthopedic rehabilitation. Thus, tactile sensors have been used in hand clinical evaluations and foot rehabilitation (Da Silva et al., 2000); (Mascaro & Asada, 2001); (Boukhenous & Attari, 2007); (Attari & Boukhenous, 2008). Human tactile sensing is achieved by means of at least four different types of receptor cells (Jayawant, 1989); (Cowie et al., 2007) and is used to feel, grasp and manipulate objects, and to assess attributes such as shape, size, texture, temperature, hardness, discontinuities such as holes or edges, and movement, including vibration. Reston and Kolesar (Reston et al., 1990) described a robotic tactile sensor manufactured from piezoelectric polyvinylidene fluoride (PVDF) film. It was not the best choice for finger mounted tactile sensors due to its limited load range and inability to measure static forces. Beebe and al (Beebe et al., 1989) developed a force sensor based on a silicon diaphragm structure instrumented with piezoresistors in Wheatstone bridge configuration. The applied force is distributed across the diaphragm via a grasping solid dome and mounted on rigid substrate with an excellent performance characteristic. In this paper a low cost tactile sensors array for the measurement of hand grasping forces is described in a first step. A second step is dedicated to the study of two-dimensional reaction forces distribution of foot during rehabilitation in the case of ankle sprain. The sensor element of the array is an easy structure based on the use of low cost Hall device and a general purpose polymer (polysiloxanes). First the elastic polymer is studied to show its ability in building such

Purpose – The aim of the research is to achieve a robot skin which is easy to use, and can detect both position and force interacted between robot and environments. Design/methodology/approach – The new type of robot skin proposed in this paper includes two functional modules – contact position sensor and contact force sensor. The contact position sensor module is based on the resistor divider principle, which consists of two perpendicular conductive fiber layers and insulated dot spacer between them. The contact force sensor module is based on capacitance change theory, which consists of two soft conductive plates and a viscoelastic layer between them. By combining the two modules, the soft robot skin was designed. Findings – Simulation and experiment results demonstrate that the proposed robot skin design is feasible and effective enough to sense contact position and contact force simultaneously. Practical implications – This robot skin is low-cost and easy to make and use, which provides safety solutions for most of the robot. Originality/value – For the first time, an integrated robot skin which can get contact position and force information simultaneously is designed. Unlike general tactile sensor matrices, this robot skin has only six leads. Furthermore, the number of leads does not increase with the enlarging of sensor area. Soft and simple structure of the robot skin makes it possible to cover any region of the robot body.

The past several decades have witnessed great progress in high‐performance field effect transistors (FET) as one of the most important electronic components. At the same time, due to their intrinsic advantages, such as multiparameter accessibility, excellent electric signal amplification function, and ease of large‐scale manufacturing, FET as tactile sensors for flexible wearable devices, artificial intelligence, Internet of Things, and other fields to perceive external stimuli has also attracted great attention and become a significant field of general concern. More importantly, FET has a unique three‐terminal structure, which enables its different components to detect external mechanics through different sensing mechanisms. On one hand, it provides an important platform to shed deep insights into the underlying mechanisms of the tactile sensors. On the other hand, these properties could in turn endow excellent components for the construction of tactile matrix sensor arrays with high quality. With special emphasis on the configuration of FETs, this review classified and summarized structure‐optimized FET tactile sensors with gate, dielectric layer, semiconductor layer, and source/drain electrodes as sensing active components, respectively. The working principles and the state‐of‐the‐art protocols in terms of high‐performance tactile sensors are detail discussed and highlighted, the innovative pixel distribution and integration analysis of the transistor sensor matrix array concerning flexible electronics are also introduced. We hope that the introduction of this review can provide some inspiration for future researchers to design and fabricate high‐performance FET‐based tactile sensor chips for flexible electronics and other fields.image

We previously proposed an artificial hollow fiber, as a new MEMS material, for the development of a fabric tactile sensor. The artificial hollow fiber is fabricated by uniformly laminating metal and insulation layers onto the surface of an elastic hollow fiber. The fabric tactile sensor is made by weaving the modified hollow fibers into a cloth. The sensor can detect the contact force by measuring changes in capacitance at the points where the warp and weft fibers intersect, and can detect 2D contact force distribution by sequentially scanning the capacitance changes at all intersecting points. We investigated the dependence of sensor output on normal load and tension. The normal load and tension were independently applied to the fiber elements in order to determine the basic characteristics of the fabric sensor. We also developed two different glove-type wearable tactile sensors. One was made by patching the sensor onto an existing glove, and the other was made by directly weaving the hollow fibers into the yarn of the glove. In experiments with the patched sensor, we confirmed that it was able to detect contact force.

In article number 1600188, Alexi Charalambides and Sarah Bergbreiter present a rapid manufacturing process using computerized numerical control (CNC) milling to create a “robot skin” with normal and shear force tactile sensing. The robot skin is made entirely of elastomer and contains tactile pixels with microscale features distributed over a large area. Using this approach, the robot skin is integrated with a 1 degree-off-reedom gripper for closed-loop grasping and slip detection.

Tactile sensing is paramount for robots operating in human-centered environments to help in understanding the interaction with objects. To enable robots with the sophisticated tactile sensing capability, researchers have developed different kinds of electronic skins for robotic hands and arms to realize the ‘sense of touch’. Recently, Stanford Structures and Composites Laboratory developed a robotic electronic skin which is based on a network of multi-modal micro-sensors. This skin can identify temperature profile and detect arm strikes by embedded sensors. However, one vital aspect of tactile sensing is yet to be investigated: sensing for the static pressure load. Current state-of-the-art tactile sensors mostly are capacitive sensors which can achieve high sensitivity. However, these sensors are liable to damage under high repeating load. In addition, capacitive sensor signals are prone to external noises which will result in complex circuitry for signal conditioning. In this work, an electromechanical-impedance based method is proposed to investigate the response of piezoelectric sensors to the static normal pressure load. The smart skin sample was firstly fabricated by embedding piezoelectric sensor into the soft silicone. Then a series of static pressure tests to the skin were performed. Test results show that this setup can reach a minimal detectable force of 0.5N by using the proposed diagnostic method. Theoretical analysis was then performed to explain the experiment results.

Fully-integrated wearable pressure sensor array enabled by highly sensitive textile-based capacitive ionotronic devices