Representation and tactile sensing of 3-D objects by a gripper finger

Robotica ◽  
1983 ◽  
Vol 1 (4) ◽  
pp. 217-222 ◽  
Author(s):  
Gen-Ichiro Kinoshita
Keyword(s):  
Tactile Sensor ◽  
Large Displacement ◽  
Tactile Sensing ◽  
Sensor Element ◽  
Maximum Displacement

SUMMARYThe tactile sensor is constructed as a part of the finger of a parallel jaw hand; it is of the size of a finger and allows for a large displacement of the sensor element in response to force. The structure of the tactile sensor incorporates 20 successively and closely aligned elements, which allow for a 2.5 mm maximum displacement for each element. In the described experiments we present the capabilities of the tactile sensor. The tactile sensor has the functions of: 1) discriminating the shape of the partial surface of an object; and 2) tracing by finger on the surface along the profile of an object.

STAND-UP MOTION SUPPORT BY A MOBILE MANIPULATOR SYSTEM WITH HIGH SPEED TACTILE SENSORS

2011 ◽  
Vol 08 (03) ◽  
pp. 181-195
Author(s):  
ZHAOXIAN XIE ◽  
HISASHI YAMAGUCHI ◽  
MASAHITO TSUKANO ◽  
AIGUO MING ◽  
MAKOTO SHIMOJO
Keyword(s):  
Fuzzy Logic ◽  
Feedback Control ◽  
Experimental Verification ◽  
High Speed ◽  
Center Of Pressure ◽  
Tactile Sensor ◽  
Mobile Manipulator ◽  
Tactile Sensing ◽  
Robot Arm ◽  
Tactile Sensors

As one of the home services by a mobile manipulator system, we are aiming at the realization of the stand-up motion support for elderly people. This work is charaterized by the use of real-time feedback control based on the information from high speed tactile sensors for detecting the contact force as well as its center of pressure between the assisted human and the robot arm. First, this paper introduces the design of the tactile sensor as well as initial experimental results to show the feasibility of the proposed system. Moreover, several fundamental tactile sensing-based motion controllers necessary for the stand-up motion support and their experimental verification are presented. Finally, an assist trajectory generation method for the stand-up motion support by integrating fuzzy logic with tactile sensing is proposed and demonstrated experimentally.

scholarly journals Hi-Speed Tactile Sensing for Array-type Tactile Sensor and Object Manipulation based on Tactile Information

2012 ◽  
Vol 25 (5) ◽  
pp. 117-125
Author(s):  
Wataru Fukui ◽  
Futoshi Kobayashi ◽  
Fumio Kojima ◽  
Hiroyuki Nakamoto ◽  
Tadashi Maeda ◽  
...  
Keyword(s):  
Tactile Sensor ◽  
Object Manipulation ◽  
Tactile Sensing ◽  
Tactile Information ◽  
Array Type

Mechanics-induced triple-mode anticounterfeiting and moving tactile sensing by simultaneously utilizing instantaneous and persistent mechanoluminescence

2019 ◽  
Vol 6 (10) ◽  
pp. 2003-2008 ◽  
Author(s):  
Zhidong Ma ◽  
Jinyu Zhou ◽  
Jiachi Zhang ◽  
Songshan Zeng ◽  
Hui Zhou ◽  
...  
Keyword(s):  
Tactile Sensor ◽  
Tactile Sensing ◽  
Triple Mode

An intriguing mechanics-induced triple-mode anticounterfeiting device and a moving tactile sensor were developed by simultaneously utilizing transient and persistent mechanoluminescence.

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%.

Force Characteristics for Fine Deformation of CMC Touch Sensor and Estimation of Force Variance Using Hybrid Tactile Sensor System

2012 ◽  
Vol 24 (3) ◽  
pp. 423-429
Author(s):  
Takuya Kawamura ◽  
◽  
Ko Nejigane ◽  
Kazuo Tani ◽  
Hironao Yamada
Keyword(s):  
Tactile Sensor ◽  
Force Sensor ◽  
Sensor System ◽  
Compression Force ◽  
Sensor Element ◽  
Silicon Rubber ◽  
Touch Sensor ◽  
Slight Movement ◽  
Force Characteristics

Having previously proposed a hybrid tactile sensor system consisting of a Carbon Micro-Coil (CMC) touch sensor and a force sensor, the authors have been developing a method of measuring deformation of micrometer order, force variance of 10 gram order, and compression force when an object touches a sensor element and moves slightly. In this paper, to measure the force variance for deformation of several micrometers using the CMC touch sensor, the force characteristics of the CMC touch sensor are investigated. The CMC sensor element is made of silicon rubber containing CMCs several micrometers in diameter. It is considered that the sensor element constitutes an LCR circuit, and the CMC touch sensor, deformed mechanically, produces signals due to the modification of the circuit. In the experiment detailed in this paper, to clarify the characteristics of the CMC sensor with respect to the parameters of force and deformation, the outputs of the CMC sensor and the force sensor for deformation in the range of 1 to 9 µm are sampled. As a result, it is found that the force characteristics of the CMC touch sensor are almost linear in terms of force variance within the range of 0 to 1 N, regardless of a compression force of less than 3 N. Finally, to evaluate the performance of the sensor system, force variance for a slight movement of an object touching the sensor element is estimated in an experiment.

scholarly journals Development of Robots with Soft Sensor Flesh for Achieving Close Interaction Behavior

2012 ◽  
Vol 2012 ◽  
pp. 1-27 ◽  
Author(s):  
Tomoaki Yoshikai ◽  
Marika Hayashi ◽  
Yui Ishizaka ◽  
Hiroko Fukushima ◽  
Asuka Kadowaki ◽  
...  
Keyword(s):  
Sensor Network ◽  
Tactile Sensor ◽  
Soft Sensor ◽  
Whole Body ◽  
Tactile Sensing ◽  
Actual Behavior ◽  
Tactile Sensors ◽  
Practical Applications ◽  
Interaction Behavior ◽  
Close Interaction

In order to achieve robots' working around humans, safe contacts against objects, humans, and environments with broad area of their body should be allowed. Furthermore, it is desirable to actively use those contacts for achieving tasks. Considering that, many practical applications will be realized by whole-body close interaction of many contacts with others. Therefore, robots are strongly expected to achieve whole-body interaction behavior with objects around them. Recently, it becomes possible to construct whole-body tactile sensor network by the advancement of research for tactile sensing system. Using such tactile sensors, some research groups have developed robots with whole-body tactile sensing exterior. However, their basic strategy is making a distributed 1-axis tactile sensor network covered with soft thin material. Those are not sufficient for achieving close interaction and detecting complicated contact changes. Therefore, we propose “Soft Sensor Flesh.” Basic idea of “Soft Sensor Flesh” is constructing robots' exterior with soft and thick foam with many sensor elements including multiaxis tactile sensors. In this paper, a constructing method for the robot systems with such soft sensor flesh is argued. Also, we develop some prototypes of soft sensor flesh and verify the feasibility of the proposed idea by actual behavior experiments.

scholarly journals Multi-frame constrained block sparse Bayesian learning for flexible tactile sensing using electrical impedance tomography

2021 ◽  
Author(s):  
Xiaojie Wang
Keyword(s):  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Bayesian Learning ◽  
Reconstruction Algorithm ◽  
Tactile Sensor ◽  
Sensor System ◽  
Tactile Sensing ◽  
Contact Detection ◽  
Sparse Bayesian Learning ◽  
Impedance Tomography

In this paper, we presented a multi-frame constrained block sparse Bayesian learning (MFC-BSBL) reconstruction algorithm to tackle the challenge of poor-quality reconstruction images in electrical impedance tomography (EIT) for tactile sensing. The fundamental idea of MFC-BSBL is to explore the sparsity, intra-frame correlation, and inter-frame correlation of impedance distributions by extending the Bayesian inference framework. To verify the proposed algorithm, we conducted numerical simulations for different cases to identify one, multiple, round, and square targets. The simulation results demonstrated that this method can effectively detect the target positions and shapes by reducing artifacts and noise in the reconstructed images. To demonstrate the application of this approach to real EIT-based tactile sensing, we conducted real-contact detection experiments using the EIT tactile sensor system. Compared with traditional methods, the tactile sensor system using the MFC-BSBL algorithm can achieve accurate contact detection and significantly reduce artifacts and noise.

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