scholarly journals Evaluation of Circle Diameter by Distributed Tactile Information in Active Tracing

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Hiroyuki Nakamoto ◽  
Futoshi Kobayashi ◽  
Fumio Kojima
Keyword(s):  
Voluntary Movement ◽  
Synthesis Method ◽  
Tactile Sensor ◽  
Active Touch ◽  
Robotic Hand ◽  
Tactile Sensors ◽  
Robotic Hands ◽  
Tactile Information ◽  
Sensor Model ◽  
Circle Diameter

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.

scholarly journals Development of Fully Flexible Tactile Pressure Sensor with Bilayer Interlaced Bumps for Robotic Grasping Applications

Micromachines ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 770
Author(s):  
Lingfeng Zhu ◽  
Yancheng Wang ◽  
Deqing Mei ◽  
Chengpeng Jiang
Keyword(s):  
Pressure Sensor ◽  
Tactile Sensor ◽  
External Pressure ◽  
Robotic Hand ◽  
Sensing Element ◽  
Tactile Sensors ◽  
Human Machine Interaction ◽  
Tactile Information ◽  
Sensing Range ◽  
Intelligent Robotics

Flexible tactile sensors have been utilized in intelligent robotics for human-machine interaction and healthcare monitoring. The relatively low flexibility, unbalanced sensitivity and sensing range of the tactile sensors are hindering the accurate tactile information perception during robotic hand grasping of different objects. This paper developed a fully flexible tactile pressure sensor, using the flexible graphene and silver composites as the sensing element and stretchable electrodes, respectively. As for the structural design of the tactile sensor, the proposed bilayer interlaced bumps can be used to convert external pressure into the stretching of graphene composites. The fabricated tactile sensor exhibits a high sensing performance, including relatively high sensitivity (up to 3.40% kPa−1), wide sensing range (200 kPa), good dynamic response, and considerable repeatability. Then, the tactile sensor has been integrated with the robotic hand finger, and the grasping results have indicated the capability of using the tactile sensor to detect the distributed pressure during grasping applications. The grasping motions, properties of the objects can be further analyzed through the acquired tactile information in time and spatial domains, demonstrating the potential applications of the tactile sensor in intelligent robotics and human-machine interfaces.

scholarly journals A Soft Tactile Sensor Based on Magnetics and Hybrid Flexible-Rigid Electronics

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5098
Author(s):  
Miguel Neto ◽  
Pedro Ribeiro ◽  
Ricardo Nunes ◽  
Lorenzo Jamone ◽  
Alexandre Bernardino ◽  
...  
Keyword(s):  
Humanoid Robot ◽  
Spin Valve ◽  
Tactile Sensor ◽  
Contact Forces ◽  
Robotic Hand ◽  
Electronic Components ◽  
Tactile Sensors ◽  
Robotic Hands ◽  
Custom Made ◽  
Comsol Simulation

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.

scholarly journals Magnetostrictive tactile sensor of detecting friction and normal force for object recognition

2020 ◽  
Vol 17 (4) ◽  
pp. 172988142093232
Author(s):  
Bing Zhang ◽  
Bowen Wang ◽  
Yunkai Li ◽  
Shaowei Jin
Keyword(s):  
Recognition Rate ◽  
Tactile Sensor ◽  
Tactile Sensing ◽  
Dynamic Force ◽  
Force Output ◽  
Tactile Sensors ◽  
Tactile Information ◽  
Normal Contact ◽  
New Type ◽  
Learning Machine

Tactile information is valuable in determining properties of objects that are inaccessible from visual perception. A new type of tangential friction and normal contact force magnetostrictive tactile sensor was developed based on the inverse magnetostrictive effect, and the force output model has been established. It can measure the exerted force in the range of 0–4 N, and it has a good response to the dynamic force in cycles of 0.25–0.5 s. We present a tactile perception strategy that a manipulator with tactile sensors in its grippers manipulates an object to measure a set of tactile features. It shows that tactile sensing system can use these features and the extreme learning machine algorithm to recognize household objects—purely from tactile sensing—from a small training set. The complex matrixes show the recognition rate is up to 83%.

scholarly journals Tactile Slippage Analysis in Optical Three-Axis Tactile Sensor for Robotic Hand

2013 ◽  
Vol 465-466 ◽  
pp. 1375-1379
Author(s):  
Hanafiah Yussof ◽  
Zahari Nur Ismarrubie ◽  
Ahmad Khushairy Makhtar ◽  
Masahiro Ohka ◽  
Siti Nora Basir
Keyword(s):  
Control Algorithm ◽  
Tactile Sensor ◽  
Robotic Hand ◽  
Robot Hand ◽  
Robot Arm ◽  
Tactile Sensors ◽  
Shear Forces ◽  
Improve Performance ◽  
Robot Arm Control ◽  
Two Phases

This paper presents experimental results of object handling motions to evaluate tactile slippage sensation in a multi fingered robot arm with optical three-axis tactile sensors installed on its two hands. The optical three-axis tactile sensor is a type of tactile sensor capable of defining normal and shear forces simultaneously. Shear force distribution is used to define slippage sensation in the robot hand system. Based on tactile slippage analysis, a new control algorithm was proposed. To improve performance during object handling motions, analysis of slippage direction is conducted. The control algorithm is classified into two phases: grasp-move-release and grasp-twist motions. Detailed explanations of the control algorithm based on the existing robot arm control system are presented. The experiment is conducted using a bottle cap, and the results reveal good performance of the proposed control algorithm to accomplish the proposed object handling motions.

scholarly journals Target Classification Method of Tactile Perception Data with Deep Learning

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1537
Author(s):  
Xingxing Zhang ◽  
Shaobo Li ◽  
Jing Yang ◽  
Qiang Bai ◽  
Yang Wang ◽  
...  
Keyword(s):  
Neural Network ◽  
Tactile Sensor ◽  
Tactile Perception ◽  
Machine Learning Algorithms ◽  
Target Classification ◽  
Clustering Method ◽  
Tactile Sensors ◽  
Residual Network ◽  
Tactile Information

In order to improve the accuracy of manipulator operation, it is necessary to install a tactile sensor on the manipulator to obtain tactile information and accurately classify a target. However, with the increase in the uncertainty and complexity of tactile sensing data characteristics, and the continuous development of tactile sensors, typical machine-learning algorithms often cannot solve the problem of target classification of pure tactile data. Here, we propose a new model by combining a convolutional neural network and a residual network, named ResNet10-v1. We optimized the convolutional kernel, hyperparameters, and loss function of the model, and further improved the accuracy of target classification through the K-means clustering method. We verified the feasibility and effectiveness of the proposed method through a large number of experiments. We expect to further improve the generalization ability of this method and provide an important reference for the research in the field of tactile perception classification.

A Low-Cost Visual Grasp Aid for Neuropathy Patients Using Flexible 3D Printed Tactile Sensors

2021 ◽  
Author(s):  
Md Omar Faruk Emon ◽  
Alex Russell ◽  
Gopal Nadkarni ◽  
Jae-Won Choi
Keyword(s):  
Electronic Device ◽  
Low Cost ◽  
Tactile Sensor ◽  
Tactile Sensors ◽  
Robotic Hands ◽  
Object A ◽  
Wearable Electronic Device ◽  
Visual Aid ◽  
Real Time Visualization ◽  
3D Printed

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.

scholarly journals Magnetic-based Soft Tactile Sensors with Deformable Continuous Force Transfer Medium for Resolving Contact Locations in Robotic Grasping and Manipulation

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4925 ◽  
Author(s):  
Alireza Mohammadi ◽  
Yangmengfei Xu ◽  
Ying Tan ◽  
Peter Choong ◽  
Denny Oetomo
Keyword(s):  
Contact Force ◽  
Learning Algorithm ◽  
Design Procedure ◽  
Tactile Sensor ◽  
Design Parameters ◽  
Robotic Hand ◽  
Tactile Sensors ◽  
Hall Effect Sensor ◽  
Grasping And Manipulation ◽  
Sensor Configuration

The resolution of contact location is important in many applications in robotics and automation. This is generally done by using an array of contact or tactile receptors, which increases cost and complexity as the required resolution or area is increased. Tactile sensors have also been developed using a continuous deformable medium between the contact and the receptors, which allows few receptors to interpolate the information among them, avoiding the weakness highlighted in the former approach. The latter is generally used to measure contact force intensity or magnitude but rarely used to identify the contact locations. This paper presents a systematic design and characterisation procedure for magnetic-based soft tactile sensors (utilizing the latter approach with the deformable contact medium) with the goal of locating the contact force location. This systematic procedure provides conditions under which design parameters can be selected, supported by a selected machine learning algorithm, to achieve the desired performance of the tactile sensor in identifying the contact location. An illustrative example, which combines a particular sensor configuration (magnetic hall effect sensor as the receptor, a selected continuous medium and a selected sensing resolution) and a specific data-driven algorithm, is used to illustrate the proposed design procedure. The results of the illustrative example design demonstrates the efficacy of the proposed design procedure and the proposed sensing strategy in identifying a contact location. The resulting sensor is also tested on a robotic hand (Allegro Hand, SimLab Co) to demonstrate its application in real-world scenarios.

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 ◽  
...  
Keyword(s):  
High Resolution ◽  
Tactile Sensor ◽  
Object Manipulation ◽  
Object Identification ◽  
Tactile Sensors ◽  
Robotic Hands ◽  
Robotic Perception ◽  
Critical Challenge

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...

scholarly journals Using Tactile Sensing to Improve the Sample Efficiency and Performance of Deep Deterministic Policy Gradients for Simulated In-Hand Manipulation Tasks

2021 ◽  
Vol 8 ◽  
Author(s):  
Andrew Melnik ◽  
Luca Lach ◽  
Matthias Plappert ◽  
Timo Korthals ◽  
Robert Haschke ◽  
...  
Keyword(s):  
Ground Truth ◽  
Tactile Sensor ◽  
Limiting Factors ◽  
Tactile Sensors ◽  
Tactile Information ◽  
Touch Sensor ◽  
Learning Techniques ◽  
Dexterous Hand ◽  
And Performance

Deep Reinforcement Learning techniques demonstrate advances in the domain of robotics. One of the limiting factors is a large number of interaction samples usually required for training in simulated and real-world environments. In this work, we demonstrate for a set of simulated dexterous in-hand object manipulation tasks that tactile information can substantially increase sample efficiency for training (by up to more than threefold). We also observe an improvement in performance (up to 46%) after adding tactile information. To examine the role of tactile-sensor parameters in these improvements, we included experiments with varied sensor-measurement accuracy (ground truth continuous values, noisy continuous values, Boolean values), and varied spatial resolution of the tactile sensors (927 sensors, 92 sensors, and 16 pooled sensor areas in the hand). To facilitate further studies and comparisons, we make these touch-sensor extensions available as a part of the OpenAI Gym Shadow-Dexterous-Hand robotics environments.

scholarly journals Fully 3D Printed Flexible, Conformal and Multi-directional Tactile Sensor with Integrated Biomimetic and Auxetic Structure

2021 ◽  
Author(s):  
Yuyang Wei ◽  
Bingqian Li ◽  
Marco Domingos ◽  
Yiming Zhu ◽  
Lingyun Yan ◽  
...  
Keyword(s):  
Lumbar Vertebra ◽  
Tactile Sensor ◽  
Tactile Feedback ◽  
Robotic Hand ◽  
Tactile Sensors ◽  
Current Sensing ◽  
Sensing Range ◽  
Sensing Technology ◽  
3D Printed ◽  
Auxetic Structure

Abstract Tactile sensors are instrumental for developing the next generation of biologically inspired robotic prostheses with tactile feedback. Despite significant advancements made in current sensing technology, several limitations still exist including the reduced sensing sensitivity under high pressure, lack of compliance of the planar sensor with working surfaces and the demand for sophisticated manufacturing processes. In this study, we investigate the feasibility of using the 3D printing technology for the rapid and simple fabrication of a new conformal tactile sensor with an improved linear sensing range. The auxetic structure is integrated with a biomimetic inter-locked papilla feature which allows to detect multi-directional stimuli. Using the proposed design, the linear sensing range is extended to 0.5MPa and responsive to normal and shear forces with the sensitivities of 2.42KPa^(-1)and 2.20N^(-1) respectively. The proposed tactile sensor was printed on the fingertip of a prosthetic robotic hand to perform the sensorimotor control, or on the proximal femur head and lumbar vertebra for monitoring the bone-on-bone load. The results have shown promising application prospects of the proposed tactile sensor.

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