scholarly journals Tactile Sensor with High-Density Microcantilever and Multiple PDMS Bumps for Contact Detection

2020 ◽  
Vol 32 (2) ◽  
pp. 297-304
Author(s):  
Tomoya Fujihashi ◽  
◽  
Fumitoshi Suga ◽  
Ryoma Araki ◽  
Jyun Kido ◽  
...  
Keyword(s):  
Contact Angle ◽  
Detection Method ◽  
Tactile Sensor ◽  
High Density ◽  
Contact Detection ◽  
Uneven Surface ◽  
Resistance Change ◽  
Contact State ◽  
Partial Contact ◽  
Contact Position

In the study, we investigated a detection method of partial contact of an object owing to curved or uneven surface of the contact object by a tactile sensor. The sensor is developed using three microcantilevers embedded in a polydimethylsiloxane (PDMS) bump. First, three bumps were employed to place a bump for each cantilever. It was possible to detect a contact position because the resistance change in the strain gauge on the cantilever under each bump significantly depended on the contact/non-contact state of each bump. Second, a tactile sensor with high-density arrangement of microcantilevers was used to detect partial or tilted contact situations. The results indicated that the output of a tactile sensor with high-density arrangement of microcantilevers reflected partial or tilted contact. It is suggested that a tactile sensor with multiple bumps and high-density microcantilevers allows for more dexterous gripping control based on the shape of the object and contact angle.

A highly-deformable piezoresistive film composed of a network of carbon blacks and highly oriented lamellae of high-density polyethylene

RSC Advances ◽  
2015 ◽  
Vol 5 (39) ◽  
pp. 31074-31080 ◽  
Author(s):  
Shaodi Zheng ◽  
Jie Deng ◽  
Luqiong Yang ◽  
Danqi Ren ◽  
Wei Yang ◽  
...  
Keyword(s):  
Electrical Resistance ◽  
High Density Polyethylene ◽  
High Density ◽  
Resistance Change ◽  
Carbon Blacks ◽  
Electrical Resistance Change

The electrical resistance change of highly extensible films consisting of a network of carbon blacks in high-density polyethylene, with different regularity of stacked lamellae, is investigated.

scholarly journals Tactile Perception for Teleoperated Robotic Exploration within Granular Media

2021 ◽  
Vol 10 (4) ◽  
pp. 1-27
Author(s):  
Shengxin Jia ◽  
Veronica J. Santos
Keyword(s):  
Granular Media ◽  
Fluid Pressure ◽  
Tactile Sensor ◽  
Tactile Perception ◽  
Test Accuracy ◽  
Contact State ◽  
Buried Objects ◽  
Media Type ◽  
Additional Information ◽  
Internal Fluid

The sense of touch is essential for locating buried objects when vision-based approaches are limited. We present an approach for tactile perception when sensorized robot fingertips are used to directly interact with granular media particles in teleoperated systems. We evaluate the effects of linear and nonlinear classifier model architectures and three tactile sensor modalities (vibration, internal fluid pressure, fingerpad deformation) on the accuracy of estimates of fingertip contact state. We propose an architecture called the Sparse-Fusion Recurrent Neural Network (SF-RNN) in which sparse features are autonomously extracted prior to fusing multimodal tactile data in a fully connected RNN input layer. The multimodal SF-RNN model achieved 98.7% test accuracy and was robust to modest variations in granular media type and particle size, fingertip orientation, fingertip speed, and object location. Fingerpad deformation was the most informative modality for haptic exploration within granular media while vibration and internal fluid pressure provided additional information with appropriate signal processing. We introduce a real-time visualization of tactile percepts for remote exploration by constructing a belief map that combines probabilistic contact state estimates and fingertip location. The belief map visualizes the probability of an object being buried in the search region and could be used for planning.

scholarly journals A Triboelectric-Based Artificial Whisker for Reactive Obstacle Avoidance and Local Mapping

Research ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Peng Xu ◽  
Xingyu Wang ◽  
Siyuan Wang ◽  
Tianyu Chen ◽  
Jianhua Liu ◽  
...  
Keyword(s):  
Obstacle Avoidance ◽  
Autonomous Robots ◽  
Tactile Sensor ◽  
Triboelectric Nanogenerator ◽  
Tactile Sensors ◽  
Biologically Inspired ◽  
External Stimulation ◽  
Autonomous Surface Vehicles ◽  
Electrostatic Induction ◽  
Contact Position

Since designing efficient tactile sensors for autonomous robots is still a challenge, this paper proposes a perceptual system based on a bioinspired triboelectric whisker sensor (TWS) that is aimed at reactive obstacle avoidance and local mapping in unknown environments. The proposed TWS is based on a triboelectric nanogenerator (TENG) and mimics the structure of rat whisker follicles. It operates to generate an output voltage via triboelectrification and electrostatic induction between the PTFE pellet and copper films (0.3 mm thickness), where a forced whisker shaft displaces a PTFE pellet (10 mm diameter). With the help of a biologically inspired structural design, the artificial whisker sensor can sense the contact position and approximate the external stimulation area, particularly in a dark environment. To highlight this sensor’s applicability and scalability, we demonstrate different functions, such as controlling LED lights, reactive obstacle avoidance, and local mapping of autonomous surface vehicles. The results show that the proposed TWS can be used as a tactile sensor for reactive obstacle avoidance and local mapping in robotics.

scholarly journals A Piezoelectric Tactile Sensor for Tissue Stiffness Detection with Arbitrary Contact Angle

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6607
Author(s):  
Yingxuan Zhang ◽  
Feng Ju ◽  
Xiaoyong Wei ◽  
Dan Wang ◽  
Yaoyao Wang
Keyword(s):  
Contact Angle ◽  
Recognition Rate ◽  
Tactile Sensor ◽  
Normal Direction ◽  
Surgical Instruments ◽  
Tissue Stiffness ◽  
Design And Optimization ◽  
Detection Model ◽  
Sensor Optimization ◽  
Simulation And Experiment

In this paper, a piezoelectric tactile sensor for detecting tissue stiffness in robot-assisted minimally invasive surgery (RMIS) is proposed. It can detect the stiffness not only when the probe is normal to the tissue surface, but also when there is a contact angle between the probe and normal direction. It solves the problem that existing sensors can only detect in the normal direction to ensure accuracy when the degree of freedom (DOF) of surgical instruments is limited. The proposed senor can distinguish samples with different stiffness and recognize lump from normal tissue effectively when the contact angle varies within [0°, 45°]. These are achieved by establishing a new detection model and sensor optimization. It deduces the influence of contact angle on stiffness detection by sensor parameters design and optimization. The detection performance of the sensor is confirmed by simulation and experiment. Five samples with different stiffness (including lump and normal samples with close stiffness) are used. Through blind recognition test in simulation, the recognition rate is 100% when the contact angle is randomly selected within 30°, 94.1% within 45°, which is 38.7% higher than the unoptimized sensor. Through blind classification test and automatic k-means clustering in experiment, the correct rate is 92% when the contact angle is randomly selected within 45°. We can get the proposed sensor can easily recognize samples with different stiffness with high accuracy which has broad application prospects in the medical field.

Improvement of the Needle-Type Dispenser for Precise Micro-Droplet Dispensation – Gap Measurement Between the Needle Tip and the Target Surface Based on Needle Vibration –

2012 ◽  
Vol 24 (2) ◽  
pp. 284-290 ◽  
Author(s):  
Shinnosuke Hirata ◽  
◽  
Kazuki Hirose ◽  
Yuuka Irie ◽  
Hisayuki Aoyama
Keyword(s):  
Detection Method ◽  
Target Surface ◽  
High Viscosity ◽  
Leaf Spring ◽  
Contact Detection ◽  
Vibration Characteristic ◽  
Glass Capillary ◽  
Needle Type ◽  
Gap Measurement ◽  
Current Systems

Micro-droplet dispensation is required in current systems or industrial equipments. However, drop-ondemand inkjet technologies are difficult to use in dispensing micro droplets from high-viscosity liquids. Therefore, the needle-type dispenser using a thin needle and a glass capillary has been developed for microdroplet dispensation. When the needle passes through the capillary with a sample liquid, a droplet of the liquid adheres to the needle tip. The micro droplet can be transcribed to the target surface by bringing the needle-tip droplet into contact with the target surface. The needle-type dispenser can dispense sub-pico-liter amounts of droplets from liquids of several hundred Pa?s. When a micro droplet is dispensed, a gap is formed between the needle tip and the target surface. Amounts of droplets are unstable, as the dispensing gaps fluctuate. Therefore, a contact-detection method of the needle-tip droplet and the target surface is proposed. The needle is vibrated by a piezoelectric actuator through a leaf spring in the proposed method. The needle-vibration characteristic is made variable by the differences in conditions between the needle-tip droplet and the target surface. Therefore, contact of the needle-tip droplet with the target surface can be detected by needle-vibration characteristics. Then, the dispensing gap can be kept constant by contact detection for dispensing accurate amounts of droplets.

RECOGNITION OF CONTACT STATE BY USING NEURAL NETWORK FOR MICROMACHINED ARRAY TYPE TACTILE SENSOR

2005 ◽  
Vol 02 (03) ◽  
pp. 181-190 ◽  
Author(s):  
SEIJI AOYAGI ◽  
TAKAAKI TANAKA ◽  
KENJI MAKIHIRA
Keyword(s):  
Neural Network ◽  
Rotation Angle ◽  
Simulated Data ◽  
Tactile Sensor ◽  
Training Data ◽  
Sensing Element ◽  
Array Type ◽  
Tactile Pattern ◽  
Hidden Layer ◽  
Contact Position

In this paper, a force sensing element having a pillar and a diaphragm is proposed and thereafter fabricated by micromachining. Piezo resistors are fabricated on a silicon diaphragm for detecting distortions caused by a force input to a pillar on the diaphragm. Since a practical arrayed sensor consisting of many of this element is still under development, the output of an assumed arrayed type tactile sensor is simulated by FEM (finite element method). Using simulated data, the possibility of tactile pattern recognition using a neural network (NN) is investigated. The learning method of NN, the number of units of the input layer and the hidden layer, as well as the number of training data are investigated for realizing high probability of recognition. The 14 subjects having different shape and size are recognized. This recognition succeeded even if the contact position and the rotation angle of these objects are changed.

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