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16 pages, 4600 KiB

Open AccessArticle

A 3-D Surface Reconstruction with Shadow Processing for Optical Tactile Sensors

by Hanjun Jiang, Yan Yan, Xiyang Zhu and Chun Zhang

Sensors 2018, 18(9), 2785; https://doi.org/10.3390/s18092785 - 24 Aug 2018

Cited by 10 | Viewed by 3819

Abstract

An optical tactile sensor technique with 3-dimension (3-D) surface reconstruction is proposed for robotic fingers. The hardware of the tactile sensor consists of a surface deformation sensing layer, an image sensor and four individually controlled flashing light emitting diodes (LEDs). The image sensor [...] Read more.

An optical tactile sensor technique with 3-dimension (3-D) surface reconstruction is proposed for robotic fingers. The hardware of the tactile sensor consists of a surface deformation sensing layer, an image sensor and four individually controlled flashing light emitting diodes (LEDs). The image sensor records the deformation images when the robotic finger touches an object. For each object, four deformation images are taken with the LEDs providing different illumination directions. Before the 3-D reconstruction, the look-up tables are built to map the intensity distribution to the image gradient data. The possible image shadow will be detected and amended. Then the 3-D depth distribution of the object surface can be reconstructed from the 2-D gradient obtained using the look-up tables. The architecture of the tactile sensor and the proposed signal processing flow have been presented in details. A prototype tactile sensor has been built. Both the simulation and experimental results have validated the effectiveness of the proposed 3-D surface reconstruction method for the optical tactile sensors. The proposed 3-D surface reconstruction method has the unique feature of image shadow detection and compensation, which differentiates itself from those in the literature. Full article

(This article belongs to the Special Issue Bio-Inspiring Sensing)

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12 pages, 4370 KiB

Open AccessArticle

Line and V-Shape Formation Based Distributed Processing for Robotic Swarms

by Jian Yang, Xin Wang and Peter Bauer

Sensors 2018, 18(8), 2543; https://doi.org/10.3390/s18082543 - 3 Aug 2018

Cited by 19 | Viewed by 3422

Abstract

Efficient distributed processing is vital for collaborative searching tasks of robotic swarm systems. Typically, those systems are decentralized, and the members have only limited communication and processing capacities. What is illustrated in this paper is a distributed processing paradigm for robotic swarms moving [...] Read more.

Efficient distributed processing is vital for collaborative searching tasks of robotic swarm systems. Typically, those systems are decentralized, and the members have only limited communication and processing capacities. What is illustrated in this paper is a distributed processing paradigm for robotic swarms moving in a line or v-shape formation. The introduced concept is capable of exploits the line and v-shape formations for 2-D filtering and processing algorithms based on a modified multi-dimensional Roesser model. The communication is only between nearest adjacent members with a simple state variable. As an example, we applied a salient region detection algorithm to the proposed framework. The simulation results indicate the designed paradigm can detect salient regions by using a moving line or v-shape formation in a scanning way. The requirement of communication and processing capability in this framework is minimal, making it a good candidate for collaborative exploration of formatted robotic swarms. Full article

(This article belongs to the Special Issue Bio-Inspiring Sensing)

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15 pages, 4453 KiB

Open AccessArticle

A Visual Cortex-Inspired Imaging-Sensor Architecture and Its Application in Real-Time Processing

by Hui Wei and Luping Wang

Sensors 2018, 18(7), 2116; https://doi.org/10.3390/s18072116 - 2 Jul 2018

Cited by 4 | Viewed by 2746

Abstract

For robots equipped with an advanced computer vision-based system, object recognition has stringent real-time requirements. When the environment becomes complicated and keeps changing, existing works (e.g., template-matching strategy and machine-learning strategy) are computationally expensive, compromising object recognition performance and even stability. In order [...] Read more.

For robots equipped with an advanced computer vision-based system, object recognition has stringent real-time requirements. When the environment becomes complicated and keeps changing, existing works (e.g., template-matching strategy and machine-learning strategy) are computationally expensive, compromising object recognition performance and even stability. In order to detect objects accurately, it is necessary to build an efficient imaging sensor architecture as the neural architecture. Inspired by the neural mechanism of primary visual cortex, this paper presents an efficient three-layer architecture and proposes an approach of constraint propagation examination to efficiently extract and process information (linear contour). Through applying this architecture in the preprocessing phase to extract lines, the running time of object detection is decreased dramatically because not only are all lines represented as very simple vectors, but also the number of lines is very limited. In terms of the second measure of improving efficiency, we apply a shape-based recognition method because it does not need any high-dimensional feature descriptor, long-term training, or time-expensive preprocessing. The final results perform well. It is proved that detection performance is good. The brain is the result of natural optimization, so we conclude that a visual cortex-inspired imaging sensor architecture can greatly improve the efficiency of information processing. Full article

(This article belongs to the Special Issue Bio-Inspiring Sensing)

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15 pages, 7140 KiB

Open AccessArticle

Vibro-Perception of Optical Bio-Inspired Fiber-Skin

by Tao Li, Sheng Zhang, Guo-Wei Lu and Yuta Sunami

Sensors 2018, 18(5), 1531; https://doi.org/10.3390/s18051531 - 12 May 2018

Cited by 8 | Viewed by 4518

Abstract

In this research, based on the principle of optical interferometry, the Mach-Zehnder and Optical Phase-locked Loop (OPLL) vibro-perception systems of bio-inspired fiber-skin are designed to mimic the tactile perception of human skin. The fiber-skin is made of the optical fiber embedded in the [...] Read more.

In this research, based on the principle of optical interferometry, the Mach-Zehnder and Optical Phase-locked Loop (OPLL) vibro-perception systems of bio-inspired fiber-skin are designed to mimic the tactile perception of human skin. The fiber-skin is made of the optical fiber embedded in the silicone elastomer. The optical fiber is an instinctive and alternative sensor for tactile perception with high sensitivity and reliability, also low cost and susceptibility to the magnetic interference. The silicone elastomer serves as a substrate with high flexibility and biocompatibility, and the optical fiber core serves as the vibro-perception sensor to detect physical motions like tapping and sliding. According to the experimental results, the designed optical fiber-skin demonstrates the ability to detect the physical motions like tapping and sliding in both the Mach-Zehnder and OPLL vibro-perception systems. For direct contact condition, the OPLL vibro-perception system shows better performance compared with the Mach-Zehnder vibro-perception system. However, the Mach-Zehnder vibro-perception system is preferable to the OPLL system in the indirect contact experiment. In summary, the fiber-skin is validated to have light touch character and excellent repeatability, which is highly-suitable for skin-mimic sensing. Full article

(This article belongs to the Special Issue Bio-Inspiring Sensing)

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14 pages, 23684 KiB

Open AccessArticle

A Hybrid Bionic Image Sensor Achieving FOV Extension and Foveated Imaging

by Qun Hao, Zihan Wang, Jie Cao and Fanghua Zhang

Sensors 2018, 18(4), 1042; https://doi.org/10.3390/s18041042 - 30 Mar 2018

Cited by 21 | Viewed by 5599

Abstract

Based on bionic compound eye and human foveated imaging mechanisms, a hybrid bionic image sensor (HBIS) is proposed in this paper to extend the field of view (FOV) with high resolution. First, the hybrid bionic imaging model was developed and the structure parameters [...] Read more.

Based on bionic compound eye and human foveated imaging mechanisms, a hybrid bionic image sensor (HBIS) is proposed in this paper to extend the field of view (FOV) with high resolution. First, the hybrid bionic imaging model was developed and the structure parameters of the HBIS were deduced. Second, the properties of the HBIS were simulated, including FOV extension, super-resolution imaging, foveal ratio and so on. Third, a prototype of the HBIS was developed to validate the theory. Imaging experiments were carried out, and the results are in accordance with the simulations, proving the potential of the HBIS for large FOV and high-resolution imaging with low cost. Full article

(This article belongs to the Special Issue Bio-Inspiring Sensing)

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5342 KiB

Open AccessArticle

A Study on the Model of Detecting the Variation of Geomagnetic Intensity Based on an Adapted Motion Strategy

by Hong Li, Mingyong Liu, Kun Liu and Feihu Zhang

Sensors 2018, 18(1), 39; https://doi.org/10.3390/s18010039 - 25 Dec 2017

Cited by 3 | Viewed by 3457

Abstract

By simulating the geomagnetic fields and analyzing thevariation of intensities, this paper presents a model for calculating the objective function ofan Autonomous Underwater Vehicle (AUV)geomagnetic navigation task. By investigating the biologically inspired strategies, the AUV successfullyreachesthe destination duringgeomagnetic navigation without using the priori [...] Read more.

By simulating the geomagnetic fields and analyzing thevariation of intensities, this paper presents a model for calculating the objective function ofan Autonomous Underwater Vehicle (AUV)geomagnetic navigation task. By investigating the biologically inspired strategies, the AUV successfullyreachesthe destination duringgeomagnetic navigation without using the priori geomagnetic map. Similar to the pattern of a flatworm, the proposed algorithm relies on a motion pattern to trigger a local searching strategy by detecting the real-time geomagnetic intensity. An adapted strategy is then implemented, which is biased on the specific target. The results show thereliabilityandeffectivenessofthe proposed algorithm. Full article

(This article belongs to the Special Issue Bio-Inspiring Sensing)

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11186 KiB

Open AccessCommunication

Mapping Sensory Spots for Moderate Temperatures on the Back of Hand

by Fan Yang, Guixu Chen, Sikai Zhou, Danhong Han, Jingjing Xu and Shengyong Xu

Sensors 2017, 17(12), 2802; https://doi.org/10.3390/s17122802 - 4 Dec 2017

Cited by 5 | Viewed by 5768

Abstract

Thermosensation with thermoreceptors plays an important role in maintaining body temperature at an optimal state and avoiding potential damage caused by harmful hot or cold environmental temperatures. In this work, the locations of sensory spots for sensing moderate temperatures of 40–50 °C on [...] Read more.

Thermosensation with thermoreceptors plays an important role in maintaining body temperature at an optimal state and avoiding potential damage caused by harmful hot or cold environmental temperatures. In this work, the locations of sensory spots for sensing moderate temperatures of 40–50 °C on the back of the hands of young Chinese people were mapped in a blind-test manner with a thermal probe of 1.0 mm spatial resolution. The number of sensory spots increased along with the testing temperature; however, the surface density of sensory spots was remarkably lower than those reported previously. The locations of the spots were irregularly distributed and subject-dependent. Even for the same subject, the number and location of sensory spots were unbalanced and asymmetric between the left and right hands. The results may offer valuable information for designing artificial electronic skin and wearable devices, as well as for clinical applications. Full article

(This article belongs to the Special Issue Bio-Inspiring Sensing)

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Review

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22 pages, 3907 KiB

Open AccessReview

Recent Development of Flexible and Stretchable Antennas for Bio-Integrated Electronics

by Jia Zhu and Huanyu Cheng

Sensors 2018, 18(12), 4364; https://doi.org/10.3390/s18124364 - 10 Dec 2018

Cited by 46 | Viewed by 7650

Abstract

Wireless technology plays an important role in data communication and power transmission, which has greatly boosted the development of flexible and stretchable electronics for biomedical applications and beyond. As a key component in wireless technology, flexible and stretchable antennas need to be flexible [...] Read more.

Wireless technology plays an important role in data communication and power transmission, which has greatly boosted the development of flexible and stretchable electronics for biomedical applications and beyond. As a key component in wireless technology, flexible and stretchable antennas need to be flexible and stretchable, enabled by the efforts with new materials or novel integration approaches with structural designs. Besides replacing the conventional rigid substrates with textile or elastomeric ones, flexible and stretchable conductive materials also need to be used for the radiation parts, including conductive textiles, liquid metals, elastomeric composites embedding conductive fillers, and stretchable structures from conventional metals. As the microwave performance of the antenna (e.g., resonance frequency, radiation pattern, and radiation efficiency) strongly depend on the mechanical deformations, the new materials and novel structures need to be carefully designed. Despite the rapid progress in the burgeoning field of flexible and stretchable antennas, plenty of challenges, as well as opportunities, still exist to achieve miniaturized antennas with a stable or tunable performance at a low cost for bio-integrated electronics. Full article

(This article belongs to the Special Issue Bio-Inspiring Sensing)

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