Method for Automatic Slippage Detection with Tactile Sensors Embedded in Prosthetic Hands

Subject. The article analyzes development trends in certain types of service robots, namely, hybrid UAVs, bionic prosthetic hands, robotic vacuum cleaners. Objectives. We focus on identifying the main trends in the development of certain types of service robots, building dynamic models of their technical indicators and models of dependence of their price and weight on absolute characteristics and technical parameters. Methods. The study employs methods of correlation and multiple regression analysis. The data of the IFR, the Remotely Piloted Aircraft System, and websites of robot manufacturers serve as the informational basis of the paper. Results. The modeling unveils positive correlation between the integrated indicator of the technical level of hybrid UAVs of convertiplane type and the wingspan. The analysis of modern bionic prosthetic hands shows that the developers focus on optimizing the structure of the prosthetic, however, as the functions of the hand improve, the weight of bionic hand increases. The main factors influencing the price of robot vacuum cleaners are their power, weight, and operating hours. Conclusions. The unit price of a complex indicator of the technical level of hybrid UAVs is lower than the corresponding indicator of fixed-wing UAVs, reflecting a greater efficiency of hybrid UAVs. The analysis of technical indicators of robotic prosthetics (using the case of bionic hands) shows that any improvement of functional characteristics leads to deterioration of weight. The analysis of technical and economic indicators of robotic vacuum cleaners reveals a positive correlation between the price and weight, operating hours and power.

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Design and Experiment of Flexible Multi-Functional Tactile Sensors for Robot Skin

ROBOT ◽

10.3724/sp.j.1218.2011.00347 ◽

2011 ◽

Vol 33 (3) ◽

pp. 347-353 ◽

Cited By ~ 6

Author(s):

Ying HUANG ◽

Wei LU ◽

Xiaowen ZHAO ◽

Chao LIAN ◽

Yunjian GE

Keyword(s):

Tactile Sensors ◽

Robot Skin

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Pressure Measurement of Planing Hull Stern Bottom by Tactile Sensors

Journal of the Society of Naval Architects of Korea ◽

10.3744/snak.2018.55.5.431 ◽

2018 ◽

Vol 55 (5) ◽

pp. 431-437

Author(s):

Sae Yong Park ◽

Jong Yeol Park ◽

Shin Hyung Lee ◽

Dong Jin Kim

Keyword(s):

Pressure Measurement ◽

Tactile Sensors

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Stable In-Grasp Manipulation with a Low-Cost Robot Hand by Using 3-Axis Tactile Sensors with a CNN

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) ◽

10.1109/iros45743.2020.9341362 ◽

2020 ◽

Author(s):

Satoshi Funabashi ◽

Tomoki Isobe ◽

Shun Ogasa ◽

Tetsuya Ogata ◽

Alexander Schmitz ◽

...

Keyword(s):

Low Cost ◽

Robot Hand ◽

Tactile Sensors

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A simplified model of a multi-jointed mechanical finger calibrated with experimental data by vision system

Proceedings of the Institution of Mechanical Engineers Part K Journal of Multi-body Dynamics ◽

10.1177/1464419320955115 ◽

2021 ◽

Vol 235 (1) ◽

pp. 164-175

Author(s):

C Cosenza ◽

V Niola ◽

S Savino

Keyword(s):

Experimental Data ◽

Vision System ◽

Control Strategies ◽

Image Correlation ◽

Robotic Hand ◽

Prosthetic Device ◽

Prosthetic Hands ◽

Mechanical Hand ◽

Free Mode ◽

Mechanical Finger

The development of suitable models for mechanical fingers, whether they are part of prosthetic device or of a robotic hand, is a powerful tool to predict the behaviour of their components since the early stages of design, especially for underactuated mechanisms. Experimental data can improve the reliability of such models and promote their application to build proper control strategies especially for prosthetic hands. Here, we have developed a multi-jointed model of a mechanical finger. The finger is part of the Federica hand: an underactuated mechanical hand that was conceived for prosthetic purpose. The model accounts for friction phenomena in the finger and it is tuned with experimental data acquired through a digital image correlation device. The model allowed us to write kinematics relations of the phalanges and evaluate finger configurations in relation to the closure velocity. Moreover, it was possible to estimate the tendon force and the work analysis occurring during the closure tasks, both in free mode and in presence of objects.

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Design of a Sensitive Balloon Sensor for Safe Human–Robot Interaction

Sensors ◽

10.3390/s21062163 ◽

2021 ◽

Vol 21 (6) ◽

pp. 2163

Author(s):

Dongjin Kim ◽

Seungyong Han ◽

Taewi Kim ◽

Changhwan Kim ◽

Doohoe Lee ◽

...

Keyword(s):

High Performance ◽

Strain Sensor ◽

High Sensitivity ◽

Human Robot Interaction ◽

Large Area ◽

Tactile Sensors ◽

Robot Interaction ◽

Mechanical Crack ◽

Flexible Strain Sensor ◽

Contact Sensing

As the safety of a human body is the main priority while interacting with robots, the field of tactile sensors has expanded for acquiring tactile information and ensuring safe human–robot interaction (HRI). Existing lightweight and thin tactile sensors exhibit high performance in detecting their surroundings. However, unexpected collisions caused by malfunctions or sudden external collisions can still cause injuries to rigid robots with thin tactile sensors. In this study, we present a sensitive balloon sensor for contact sensing and alleviating physical collisions over a large area of rigid robots. The balloon sensor is a pressure sensor composed of an inflatable body of low-density polyethylene (LDPE), and a highly sensitive and flexible strain sensor laminated onto it. The mechanical crack-based strain sensor with high sensitivity enables the detection of extremely small changes in the strain of the balloon. Adjusting the geometric parameters of the balloon allows for a large and easily customizable sensing area. The weight of the balloon sensor was approximately 2 g. The sensor is employed with a servo motor and detects a finger or a sheet of rolled paper gently touching it, without being damaged.

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A Vibrissa-Inspired Highly Flexible Tactile Sensor: Scanning 3D Object Surfaces Providing Tactile Images

Sensors ◽

10.3390/s21051572 ◽

2021 ◽

Vol 21 (5) ◽

pp. 1572

Author(s):

Lukas Merker ◽

Joachim Steigenberger ◽

Rafael Marangoni ◽

Carsten Behn

Keyword(s):

Steel Wire ◽

Sense Organ ◽

Tactile Sensor ◽

Tactile Sensors ◽

Measuring Device ◽

3D Object ◽

Torque Transducer ◽

Sense Of Touch ◽

Important Basis ◽

Support Reactions

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.

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Hierarchical Tactile Sensation Integration from Prosthetic Fingertips Enables Multi-Texture Surface Recognition

Sensors ◽

10.3390/s21134324 ◽

2021 ◽

Vol 21 (13) ◽

pp. 4324

Author(s):

Moaed A. Abd ◽

Rudy Paul ◽

Aparna Aravelli ◽

Ou Bai ◽

Leonel Lagos ◽

...

Keyword(s):

Machine Learning ◽

Learning Algorithms ◽

Machine Learning Algorithms ◽

Sliding Contact ◽

Tactile Sensation ◽

Support Vector ◽

Textured Surfaces ◽

K Nearest Neighbor ◽

Tactile Sensors ◽

Time Frequency

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.

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