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Special Issue "Biomimetic Sensors, Actuators and Integrated Systems"

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (29 December 2011)

Special Issue Editors

Guest Editor
Dr. Trung Dung Ngo (Website)

The More Than One Robotics Laboratory, University of Brunei Darussalam, Brunei Darussalam
Interests: bio-inspired robotics; biological computation; large-scale autonomous systems; signal processing in embedded systems; sensor networks; intelligent building blocks; ambient intelligence
Guest Editor
Dr. Frank Nickols (Website)

The School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang, Avenue, Singapore 639798, Singapore (Visiting from University of Brunei Darussalam)
Interests: biomimetic skeletal muscle (up to 300W mechanical output power); eagle bird flight robotics; multi-agent hexapod robotics; biomimetic inverse kinematics of muscle control; dynamic biomimetic robotics

Special Issue Information

Dear Colleagues,

It is well known that biological organisms have evolved via natural selection over unimaginable epochs of time. Such organisms serve as an awesome, rich and virtually endless inspirational source for scientific researchers. The wide ranging and diverse principles of biological organisms can be copied, mimicked or adapted by engineers in the design and innovation of engineering systems. Two particular areas for which there is still much to be discovered are firstly from the ingenious sophistication of animal and vegetable sensors together with their biological signal processing and secondly the locomotion dexterity of moving creatures utilising biological actuators together with their biological signal control. Biological organisms are masters of multi-disciplined scientific synergy. For example, skeletal muscle tissue is a brain triggered, force producing mechanism that draws upon the phenomena of physics, chemistry and electricity to ultimately produce activation of an ingenious complex nano-mechanical structure. Studying, replicating and integrating these biological mechanisms into man-made devices is providing blueprints for a new generation of bio-engineering or biomimicking products possessing previously unattainable abilities. These improvements require the engagement of scientists and researchers from wide ranging fields of, for example, biology, engineering, materials science, chemistry, physical science, zoology, linguistics/communication science and scientific philosophy. Such work will then enable the synthesis, design, and development of new technologies through the observation and investigation of living organisms in nature.

This special issue of Sensors aims at gathering recent research work that outlines the mechanisms, applications and challenges concerning biomimetic sensors, actuators, and their integrated systems. Topics in this issue include, but are not limited to, the following:

  • design principles, prototyping and development of biomimetic sensors and actuators
  • system integration and control of biomimetic sensors and actuators
  • methods, techniques and algorithms of bio-inspired sensor measurement, estimation and calibration
  • biomechanics and locomotion control algorithms
  • bio-signal amplification techniques and processing algorithms
  • smart materials and fabrication technologies
  • philosophy of biomimetic sensors, actuators, and integrated systems in science and applications
  • applications of biomimetic sensors, actuators, and integrated systems

Dr. Trung Dung Ngo
Dr. Frank Nickols
Guest Editors

Keywords

  • biosensors
  • biomechanics
  • sensor-motor integration
  • smart materials
  • bio-signal processing
  • bio-inspired systems and control
  • applications of bio-inspired systems

Published Papers (8 papers)

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Research

Open AccessArticle Integrating Iris and Signature Traits for Personal Authentication Using User-SpecificWeighting
Sensors 2012, 12(4), 4324-4338; doi:10.3390/s120404324
Received: 7 March 2012 / Revised: 22 March 2012 / Accepted: 22 March 2012 / Published: 29 March 2012
Cited by 2 | PDF Full-text (182 KB) | HTML Full-text | XML Full-text
Abstract
Biometric systems based on uni-modal traits are characterized by noisy sensor data, restricted degrees of freedom, non-universality and are susceptible to spoof attacks. Multi-modal biometric systems seek to alleviate some of these drawbacks by providing multiple evidences of the same identity. In [...] Read more.
Biometric systems based on uni-modal traits are characterized by noisy sensor data, restricted degrees of freedom, non-universality and are susceptible to spoof attacks. Multi-modal biometric systems seek to alleviate some of these drawbacks by providing multiple evidences of the same identity. In this paper, a user-score-based weighting technique for integrating the iris and signature traits is presented. This user-specific weighting technique has proved to be an efficient and effective fusion scheme which increases the authentication accuracy rate of multi-modal biometric systems. The weights are used to indicate the importance of matching scores output by each biometrics trait. The experimental results show that our biometric system based on the integration of iris and signature traits achieve a false rejection rate (FRR) of 0.08% and a false acceptance rate (FAR) of 0.01%. Full article
(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)
Open AccessArticle A Neuro-Inspired Spike-Based PID Motor Controller for Multi-Motor Robots with Low Cost FPGAs
Sensors 2012, 12(4), 3831-3856; doi:10.3390/s120403831
Received: 5 February 2012 / Revised: 12 March 2012 / Accepted: 21 March 2012 / Published: 26 March 2012
Cited by 15 | PDF Full-text (811 KB) | HTML Full-text | XML Full-text
Abstract
In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could [...] Read more.
In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN), which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control. Full article
(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)
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Open AccessArticle Electrical Model of a Carbon-Polymer Composite (CPC) Collision Detector
Sensors 2012, 12(2), 1950-1966; doi:10.3390/s120201950
Received: 29 December 2011 / Revised: 24 January 2012 / Accepted: 6 February 2012 / Published: 10 February 2012
Cited by 7 | PDF Full-text (2070 KB) | HTML Full-text | XML Full-text
Abstract
We present a study of an electrical model of electromechanically active carbon-polymer composite (CPC) with carbide-derived carbon (CDC) electrodes. The major focus is on investigation of surface electrode behavior upon external bending of the material. We show that electrical impedance measured from [...] Read more.
We present a study of an electrical model of electromechanically active carbon-polymer composite (CPC) with carbide-derived carbon (CDC) electrodes. The major focus is on investigation of surface electrode behavior upon external bending of the material. We show that electrical impedance measured from the surface of the CDC-based CPC can be used to determine the curvature of the material and, hence, the tip displacement of a CPC laminate in a cantilever configuration. It is also shown that by measuring surface signals in the process of an actuator’s work-cycle, we obtain a self-sensing collision-detecting CPC actuator that can be considered as a counterpart of biomimetic vibrissae. Full article
(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)
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Open AccessArticle Online Assessment of Human-Robot Interaction for Hybrid Control of Walking
Sensors 2012, 12(1), 215-225; doi:10.3390/s120100215
Received: 3 November 2011 / Revised: 7 December 2011 / Accepted: 16 December 2011 / Published: 27 December 2011
Cited by 8 | PDF Full-text (1720 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Restoration of walking ability of Spinal Cord Injury subjects can be achieved by different approaches, as the use of robotic exoskeletons or electrical stimulation of the user’s muscles. The combined (hybrid) approach has the potential to provide a solution to the drawback [...] Read more.
Restoration of walking ability of Spinal Cord Injury subjects can be achieved by different approaches, as the use of robotic exoskeletons or electrical stimulation of the user’s muscles. The combined (hybrid) approach has the potential to provide a solution to the drawback of each approach. Specific challenges must be addressed with specific sensory systems and control strategies. In this paper we present a system and a procedure to estimate muscle fatigue from online physical interaction assessment to provide hybrid control of walking, regarding the performances of the muscles under stimulation. Full article
(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)
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Open AccessArticle On the Biomimetic Design of Agile-Robot Legs
Sensors 2011, 11(12), 11305-11334; doi:10.3390/s111211305
Received: 3 November 2011 / Revised: 24 November 2011 / Accepted: 24 November 2011 / Published: 28 November 2011
Cited by 8 | PDF Full-text (26810 KB) | HTML Full-text | XML Full-text
Abstract
The development of functional legged robots has encountered its limits in human-made actuation technology. This paper describes research on the biomimetic design of legs for agile quadrupeds. A biomimetic leg concept that extracts key principles from horse legs which are responsible for [...] Read more.
The development of functional legged robots has encountered its limits in human-made actuation technology. This paper describes research on the biomimetic design of legs for agile quadrupeds. A biomimetic leg concept that extracts key principles from horse legs which are responsible for the agile and powerful locomotion of these animals is presented. The proposed biomimetic leg model defines the effective leg length, leg kinematics, limb mass distribution, actuator power, and elastic energy recovery as determinants of agile locomotion, and values for these five key elements are given. The transfer of the extracted principles to technological instantiations is analyzed in detail, considering the availability of current materials, structures and actuators. A real leg prototype has been developed following the biomimetic leg concept proposed. The actuation system is based on the hybrid use of series elasticity and magneto-rheological dampers which provides variable compliance for natural motion. From the experimental evaluation of this prototype, conclusions on the current technological barriers to achieve real functional legged robots to walk dynamically in agile locomotion are presented. Full article
(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)
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Open AccessArticle Selective Change Driven Imaging: A Biomimetic Visual Sensing Strategy
Sensors 2011, 11(11), 11000-11020; doi:10.3390/s111111000
Received: 15 October 2011 / Revised: 15 November 2011 / Accepted: 18 November 2011 / Published: 23 November 2011
Cited by 3 | PDF Full-text (2383 KB) | HTML Full-text | XML Full-text
Abstract
Selective Change Driven (SCD) Vision is a biologically inspired strategy for acquiring, transmitting and processing images that significantly speeds up image sensing. SCD vision is based on a new CMOS image sensor which delivers, ordered by the absolute magnitude of its change, [...] Read more.
Selective Change Driven (SCD) Vision is a biologically inspired strategy for acquiring, transmitting and processing images that significantly speeds up image sensing. SCD vision is based on a new CMOS image sensor which delivers, ordered by the absolute magnitude of its change, the pixels that have changed after the last time they were read out. Moreover, the traditional full frame processing hardware and programming methodology has to be changed, as a part of this biomimetic approach, to a new processing paradigm based on pixel processing in a data flow manner, instead of full frame image processing. Full article
(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)
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Open AccessArticle Artificial Skin Ridges Enhance Local Tactile Shape Discrimination
Sensors 2011, 11(9), 8626-8642; doi:10.3390/s110908626
Received: 9 August 2011 / Revised: 31 August 2011 / Accepted: 2 September 2011 / Published: 5 September 2011
Cited by 5 | PDF Full-text (443 KB) | HTML Full-text | XML Full-text
Abstract
One of the fundamental requirements for an artificial hand to successfully grasp and manipulate an object is to be able to distinguish different objects’ shapes and, more specifically, the objects’ surface curvatures. In this study, we investigate the possibility of enhancing the [...] Read more.
One of the fundamental requirements for an artificial hand to successfully grasp and manipulate an object is to be able to distinguish different objects’ shapes and, more specifically, the objects’ surface curvatures. In this study, we investigate the possibility of enhancing the curvature detection of embedded tactile sensors by proposing a ridged fingertip structure, simulating human fingerprints. In addition, a curvature detection approach based on machine learning methods is proposed to provide the embedded sensors with the ability to discriminate the surface curvature of different objects. For this purpose, a set of experiments were carried out to collect tactile signals from a 2 × 2 tactile sensor array, then the signals were processed and used for learning algorithms. To achieve the best possible performance for our machine learning approach, three different learning algorithms of Naïve Bayes (NB), Artificial Neural Networks (ANN), and Support Vector Machines (SVM) were implemented and compared for various parameters. Finally, the most accurate method was selected to evaluate the proposed skin structure in recognition of three different curvatures. The results showed an accuracy rate of 97.5% in surface curvature discrimination. Full article
(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)
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Open AccessArticle An Efficient Direction Field-Based Method for the Detection of Fasteners on High-Speed Railways
Sensors 2011, 11(8), 7364-7381; doi:10.3390/s110807364
Received: 28 June 2011 / Revised: 14 July 2011 / Accepted: 15 July 2011 / Published: 25 July 2011
Cited by 7 | PDF Full-text (2868 KB) | HTML Full-text | XML Full-text
Abstract
Railway inspection is an important task in railway maintenance to ensure safety. The fastener is a major part of the railway which fastens the tracks to the ground. The current article presents an efficient method to detect fasteners on the basis of [...] Read more.
Railway inspection is an important task in railway maintenance to ensure safety. The fastener is a major part of the railway which fastens the tracks to the ground. The current article presents an efficient method to detect fasteners on the basis of image processing and pattern recognition techniques, which can be used to detect the absence of fasteners on the corresponding track in high-speed(up to 400 km/h). The Direction Field is extracted as the feature descriptor for recognition. In addition, the appropriate weight coefficient matrix is presented for robust and rapid matching in a complex environment. Experimental results are presented to show that the proposed method is computation efficient and robust for the detection of fasteners in a complex environment. Through the practical device fixed on the track inspection train, enough fastener samples are obtained, and the feasibility of the method is verified at 400 km/h. Full article
(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)

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