Skin-inspired quadruple tactile sensors integrated on a robot hand enable object recognition

2020 ◽  
Vol 5 (49) ◽  
pp. eabc8134
Author(s):  
Guozhen Li ◽  
Shiqiang Liu ◽  
Liangqi Wang ◽  
Rong Zhu
Keyword(s):  
Object Recognition ◽  
Tactile Sensor ◽  
Object Identification ◽  
Robot Hand ◽  
Tactile Sensors ◽  
Object Temperature ◽  
Environment Temperature ◽  
Robot Hands ◽  
Different Shapes ◽  
Material Measure

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.

Nonparametric Object Recognition With a New Tactile Sensor

1992 ◽  
Author(s):  
S. Unsal ◽  
A. Shirkhodaie ◽  
A. H. Soni
Keyword(s):  
Decision Making ◽  
Object Recognition ◽  
Sensory Information ◽  
Tactile Sensor ◽  
Operating Environment ◽  
Tactile Sensors ◽  
Binary Array ◽  
Software And Hardware ◽  
Robotic Applications

Abstract Adding sensing capability to a robot provides the robot with intelligent perception capability and flexibility of decision making. To perform intelligent tasks, robots are highly required to perceive their operating environment, and react accordingly. With this regard, tactile sensors offer to extend the scope of intelligence of a robot for performing tasks which require object touching, recognition, and manipulation. This paper presents the design of an inexpensive pneumatic binary-array tactile sensor for such robotic applications. The paper describes some of the techniques implemented for object recognition from binary sensory information. Furthermore, it details the development of software and hardware which facilitate the sensor to provide useful information to a robot so that the robot perceives its operating environment during manipulation of objects.

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 Tactile Object Recognition for Humanoid Robots Using New Designed Piezoresistive Tactile Sensor and DCNN

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6024
Author(s):  
Somchai Pohtongkam ◽  
Jakkree Srinonchat
Keyword(s):  
Object Recognition ◽  
Humanoid Robot ◽  
Sensor Array ◽  
Recognition Rate ◽  
Tactile Sensor ◽  
Humanoid Robots ◽  
Superior Performance ◽  
Robot Hand ◽  
Sensing Element ◽  
Tactile Sensor Array

A tactile sensor array is a crucial component for applying physical sensors to a humanoid robot. This work focused on developing a palm-size tactile sensor array (56.0 mm × 56.0 mm) to apply object recognition for the humanoid robot hand. This sensor was based on a PCB technology operating with the piezoresistive principle. A conductive polymer composites sheet was used as a sensing element and the matrix array of this sensor was 16 × 16 pixels. The sensitivity of this sensor was evaluated and the sensor was installed on the robot hand. The tactile images, with resolution enhancement using bicubic interpolation obtained from 20 classes, were used to train and test 19 different DCNNs. InceptionResNetV2 provided superior performance with 91.82% accuracy. However, using the multimodal learning method that included InceptionResNetV2 and XceptionNet, the highest recognition rate of 92.73% was achieved. Moreover, this recognition rate improved when the object exploration was applied to demonstrate.

scholarly journals Soft Biomimetic Optical Tactile Sensing with the TacTip: A Review

2021 ◽  
Author(s):  
Nathan Lepora
Keyword(s):  
Tactile Sensor ◽  
Step Change ◽  
Tactile Sensors ◽  
The Past ◽  
Robot Hands ◽  
Human Touch ◽  
Skin Morphology ◽  
Sense Of Touch ◽  
And Control ◽  
Human Sense

<div>Reproducing the capabilities of the human sense of touch in machines is an important step in enabling robot manipulation to have the ease of human dexterity. A combination of robotic technologies will be needed, including soft robotics, biomimetics and the high-resolution sensing offered by optical tactile sensors. This combination is considered here as a SoftBOT (Soft Biomimetic Optical Tactile) sensor. This article reviews the BRL TacTip as a prototypical example of such a sensor. Topics include the relation between artificial skin morphology and the transduction principles of human touch, the nature and benefits of tactile shear sensing, 3D printing for fabrication and integration into robot hands, the application of AI to tactile perception and control, and the recent step-change in capabilities due to deep learning. This review consolidates those advances from the past decade to indicate a path for robots to reach human-like dexterity.</div><div><br></div>

Object Recognition Through Active Exploration Using a Multi-Fingered Robot Hand with 3D Tactile Sensors

2018 ◽  
Vol 2018 (0) ◽  
pp. 1P2-G16
Author(s):  
Shun OGASA ◽  
Shu MORIKUNI ◽  
Satoshi FUNABASHI ◽  
Alexander SCHMITZ ◽  
Tito Pradhono TOMO ◽  
...  
Keyword(s):  
Object Recognition ◽  
Robot Hand ◽  
Tactile Sensors ◽  
Active Exploration

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 Soft Magnetic Powdery Sensor for Tactile Sensing

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2677 ◽  
Author(s):  
Shunsuke Nagahama ◽  
Kayo Migita ◽  
Shigeki Sugano
Keyword(s):  
Magnetic Field ◽  
Flexible Electronics ◽  
Tactile Sensor ◽  
Contact Forces ◽  
Tactile Sensors ◽  
Soft Magnetic ◽  
Initial State ◽  
Response Characteristics ◽  
Flexible Material ◽  
Robot Hands

Soft resistive tactile sensors are versatile devices with applications in next-generation flexible electronics. We developed a novel type of soft resistive tactile sensor called a soft magnetic powdery sensor (soft-MPS) and evaluated its response characteristics. The soft-MPS comprises ferromagnetic powder that is immobilized in a liquid resin such as polydimethylsiloxane (PDMS) after orienting in a magnetic field. On applying an external force to the sensor, the relative distance between particles changes, thereby affecting its resistance. Since the ferromagnetic powders are in contact from the initial state, they have the ability to detect small contact forces compared to conventional resistive sensors in which the conductive powder is dispersed in a flexible material. The sensor unit can be made in any shape by controlling the layout of the magnetic field. Soft-MPSs with different hardnesses that could detect small forces were fabricated. The soft-MPS could be applied to detect collisions in robot hands/arms or in ultra-sensitive touchscreen devices.

scholarly journals Soft Biomimetic Optical Tactile Sensing with the TacTip: A Review

2021 ◽  
Author(s):  
Nathan Lepora
Keyword(s):  
Tactile Sensor ◽  
Step Change ◽  
Tactile Sensors ◽  
The Past ◽  
Robot Hands ◽  
Human Touch ◽  
Skin Morphology ◽  
Sense Of Touch ◽  
And Control ◽  
Human Sense

<div>Reproducing the capabilities of the human sense of touch in machines is an important step in enabling robot manipulation to have the ease of human dexterity. A combination of robotic technologies will be needed, including soft robotics, biomimetics and the high-resolution sensing offered by optical tactile sensors. This combination is considered here as a SoftBOT (Soft Biomimetic Optical Tactile) sensor. This article reviews the BRL TacTip as a prototypical example of such a sensor. Topics include the relation between artificial skin morphology and the transduction principles of human touch, the nature and benefits of tactile shear sensing, 3D printing for fabrication and integration into robot hands, the application of AI to tactile perception and control, and the recent step-change in capabilities due to deep learning. This review consolidates those advances from the past decade to indicate a path for robots to reach human-like dexterity.</div><div><br></div>

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