A High-Resolution, Ultrabroad-Range and Sensitive Capacitive Tactile Sensor based on CNTs/PDMS Composite for Robotic Hands

Nanoscale ◽  
2021 ◽  
Author(s):  
Xiang Fu ◽  
Jiqiang Zhang ◽  
Jianliang Xiao ◽  
Yuran Kang ◽  
Longteng Yu ◽  
...  

Tactile sensors are of great significance for robotic perception improvement to realize stable object manipulation and accurate object identification. To date, it remains a critical challenge to develop a broad-range...

2018 ◽  
Vol 15 (4) ◽  
pp. 172988141878363 ◽  
Author(s):  
Utku Büyükşahin ◽  
Ahmet Kırlı

Tactile sensors are commonly a coordinated group of receptors forming a matrix array meant to measure force or pressure similar to the human skin. Optic-based tactile sensors are flexible, sensitive, and fast; however, the human fingertip’s spatial resolution, which can be regarded as the desired spatial resolution, still could not be reached because of their bulky nature. This article proposes a novel and patented optic-based tactile sensor design, in which fiber optic cables are used to increase the number of sensory receptors per square centimeter. The proposed human-like high-resolution tactile sensor design is based on simple optics and image processing techniques, and it enables high spatial resolution and easy data acquisition at low cost. This design proposes using the change in the intesity of the light occured due to the deformation on contact/measurement surface. The main idea is using fiber optic cables as the afferents of the human physiology which can have 9 µm diameters for both delivering and receiving light beams. The variation of the light intensity enters sequent mathematical models as the input, then, the displacement, the force, and the pressure data are evaluated as the outputs. A prototype tactile sensor is manufactured with 1-mm spatial and 0.61-kPa pressure measurement resolution with 0–15.6 N/cm2 at 30 Hz sampling frequency. Experimental studies with different scenarios are conducted to demonstrate how this state-of-the-art design worked and to evaluate its performance. The overall accuracy of the first prototype, based on different scenarios, is calculated as 93%. This performance is regarded as promising for further developments and applications such as grasp control or haptics.


2021 ◽  
Author(s):  
Md Omar Faruk Emon ◽  
Alex Russell ◽  
Gopal Nadkarni ◽  
Jae-Won Choi

Abstract Neuropathy is a nerve-damaging disease that causes those affected to lose feeling in their otherwise functional limbs. It can cause permanent numbing to the peripheral limb of a patient such as a hand or foot. In this report, we present a real-time visualization aid for grasp realization that can be used by patients experiencing numbness of the limb. This wearable electronic device was developed on an open-source microcontroller-based platform. This is a very simple and inexpensive solution. It is referred to as a NeuroGlove, and it provides patients with a visual light scale to allow them to understand the strength of the grasp they have on any object. A soft tactile sensor was additively manufactured by utilizing a multi-material direct-print system. The sensor consists of an ionic liquid-based pressure-sensitive membrane, stretchable electrodes, and insulation membranes. The printed flexible polymeric sensor was evaluated under varying forces. Next, the fabricated sensor was integrated with a microcontroller board where it was programmed to respond in a light scale according to the applied force on the sensor. Finally, the sensor-microcontroller system was installed on a glove to demonstrate a wearable visual aid for neuropathy patients. Additive manufacturing offers the ability for customization in a design, material, and geometry that could potentially lead to printing sensors on prosthetic or robotic hands.


2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Hiroyuki Nakamoto ◽  
Futoshi Kobayashi ◽  
Fumio Kojima

Active touch with voluntary movement on the surface of an object is important for human to obtain the local and detailed features on it. In addition, the active touch is considered to enhance the human spatial resolution. In order to improve dexterity performance of multifinger robotic hands, it is necessary to study an active touch method for robotic hands. In this paper, first, we define four requirements of a tactile sensor for active touch and design a distributed tactile sensor model, which can measure a distribution of compressive deformation. Second, we suggest a measurement process with the sensor model, a synthesis method of distributed deformations. In the experiments, a five-finger robotic hand with tactile sensors traces on the surface of cylindrical objects and evaluates the diameters. We confirm that the hand can obtain more information of the diameters by tracing the finger.


Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5098
Author(s):  
Miguel Neto ◽  
Pedro Ribeiro ◽  
Ricardo Nunes ◽  
Lorenzo Jamone ◽  
Alexandre Bernardino ◽  
...  

Tactile sensing is crucial for robots to manipulate objects successfully. However, integrating tactile sensors into robotic hands is still challenging, mainly due to the need to cover small multi-curved surfaces with several components that must be miniaturized. In this paper, we report the design of a novel magnetic-based tactile sensor to be integrated into the robotic hand of the humanoid robot Vizzy. We designed and fabricated a flexible 4 × 2 matrix of Si chips of magnetoresistive spin valve sensors that, coupled with a single small magnet, can measure contact forces from 0.1 to 5 N on multiple locations over the surface of a robotic fingertip; this design is innovative with respect to previous works in the literature, and it is made possible by careful engineering and miniaturization of the custom-made electronic components that we employ. In addition, we characterize the behavior of the sensor through a COMSOL simulation, which can be used to generate optimized designs for sensors with different geometries.


2020 ◽  
Vol 5 (49) ◽  
pp. eabc8134
Author(s):  
Guozhen Li ◽  
Shiqiang Liu ◽  
Liangqi Wang ◽  
Rong Zhu

Robot hands with tactile perception can improve the safety of object manipulation and also improve the accuracy of object identification. Here, we report the integration of quadruple tactile sensors onto a robot hand to enable precise object recognition through grasping. Our quadruple tactile sensor consists of a skin-inspired multilayer microstructure. It works as thermoreceptor with the ability to perceive thermal conductivity of a material, measure contact pressure, as well as sense object temperature and environment temperature simultaneously and independently. By combining tactile sensing information and machine learning, our smart hand has the capability to precisely recognize different shapes, sizes, and materials in a diverse set of objects. We further apply our smart hand to the task of garbage sorting and demonstrate a classification accuracy of 94% in recognizing seven types of garbage.


2019 ◽  
Vol 16 (03) ◽  
pp. 1940002 ◽  
Author(s):  
Akihiko Yamaguchi ◽  
Christopher G. Atkeson

This paper introduces a vision-based tactile sensor FingerVision, and explores its usefulness in tactile behaviors. FingerVision consists of a transparent elastic skin marked with dots, and a camera that is easy to fabricate, low cost, and physically robust. Unlike other vision-based tactile sensors, the complete transparency of the FingerVision skin provides multimodal sensation. The modalities sensed by FingerVision include distributions of force and slip, and object information such as distance, location, pose, size, shape, and texture. The slip detection is very sensitive since it is obtained by computer vision directly applied to the output from the FingerVision camera. It provides high-resolution slip detection, which does not depend on the contact force, i.e., it can sense slip of a lightweight object that generates negligible contact force. The tactile behaviors explored in this paper include manipulations that utilize this feature. For example, we demonstrate that grasp adaptation with FingerVision can grasp origami, and other deformable and fragile objects such as vegetables, fruits, and raw eggs.


Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1572
Author(s):  
Lukas Merker ◽  
Joachim Steigenberger ◽  
Rafael Marangoni ◽  
Carsten Behn

Just as the sense of touch complements vision in various species, several robots could benefit from advanced tactile sensors, in particular when operating under poor visibility. A prominent tactile sense organ, frequently serving as a natural paragon for developing tactile sensors, is the vibrissae of, e.g., rats. Within this study, we present a vibrissa-inspired sensor concept for 3D object scanning and reconstruction to be exemplarily used in mobile robots. The setup consists of a highly flexible rod attached to a 3D force-torque transducer (measuring device). The scanning process is realized by translationally shifting the base of the rod relative to the object. Consequently, the rod sweeps over the object’s surface, undergoing large bending deflections. Then, the support reactions at the base of the rod are evaluated for contact localization. Presenting a method of theoretically generating these support reactions, we provide an important basis for future parameter studies. During scanning, lateral slip of the rod is not actively prevented, in contrast to literature. In this way, we demonstrate the suitability of the sensor for passively dragging it on a mobile robot. Experimental scanning sweeps using an artificial vibrissa (steel wire) of length 50 mm and a glass sphere as a test object with a diameter of 60 mm verify the theoretical results and serve as a proof of concept.


2021 ◽  
Vol 6 (51) ◽  
pp. eabc8801
Author(s):  
Youcan Yan ◽  
Zhe Hu ◽  
Zhengbao Yang ◽  
Wenzhen Yuan ◽  
Chaoyang Song ◽  
...  

Human skin can sense subtle changes of both normal and shear forces (i.e., self-decoupled) and perceive stimuli with finer resolution than the average spacing between mechanoreceptors (i.e., super-resolved). By contrast, existing tactile sensors for robotic applications are inferior, lacking accurate force decoupling and proper spatial resolution at the same time. Here, we present a soft tactile sensor with self-decoupling and super-resolution abilities by designing a sinusoidally magnetized flexible film (with the thickness ~0.5 millimeters), whose deformation can be detected by a Hall sensor according to the change of magnetic flux densities under external forces. The sensor can accurately measure the normal force and the shear force (demonstrated in one dimension) with a single unit and achieve a 60-fold super-resolved accuracy enhanced by deep learning. By mounting our sensor at the fingertip of a robotic gripper, we show that robots can accomplish challenging tasks such as stably grasping fragile objects under external disturbance and threading a needle via teleoperation. This research provides new insight into tactile sensor design and could be beneficial to various applications in robotics field, such as adaptive grasping, dexterous manipulation, and human-robot interaction.


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