985 resultados para bio-inspired foams


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Nature is a school for scientists and engineers. Inherent multiscale structures of biological materials exhibit multifunctional integration. In nature, the lotus, the water strider, and the flying bird evolved different and optimized biological solutions to survive. In this contribution, inspired by the optimized solutions from the lotus leaf with superhydrophobic self-cleaning, the water strider leg with durable and robust superhydrophobicity, and the lightweight bird bone with hollow structures, multifunctional metallic foams with multiscale structures are fabricated, demonstrating low adhesive superhydrophobic self-cleaning, striking loading capacity, and superior repellency towards different corrosive solutions. This approach provides an effective avenue to the development of water strider robots and other aquatic smart devices floating on water. Furthermore, the resultant multifunctional metallic foam can be used to construct an oil/water separation apparatus, exhibiting a high separation efficiency and long-term repeatability. The presented approach should provide a promising solution for the design and construction of other multifunctional metallic foams in a large scale for practical applications in the petro-chemical field. Optimized biological solutions continue to inspire and to provide design idea for the construction of multiscale structures with multifunctional integration. Inspired by the optimized biological solutions from the lotus leaf with superhydrophobic self-cleaning, the water strider leg with durable and robust superhydrophobicity, and the lightweight bird bone with hollow structures, multifunctional metallic foams with multiscale structures are fabricated, demonstrating low adhesive superhydrophobic self-cleaning, striking loading capacity, stable corrosion resistance, and oil/water separation.

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The implementation of a robotic security solution generally requires one algorithm to route the robot around the environment and another algorithm to perform anomaly detection. Solutions to the routing problem require the robot to have a good estimate of its own pose. We present a novel security system that uses metrics generated by the localisation algorithm to perform adaptive anomaly detection. The localisation algorithm is a vision-based SLAM solution called RatSLAM, based on mechanisms within the hippocampus. The anomaly detection algorithm is based on the mechanisms used by the immune system to identify threats to the body. The system is explored using data gathered within an unmodified office environment. It is shown that the algorithm successfully reacts to the presence of people and objects in areas where they are not usually present and is tolerised against the presence of people in environments that are usually dynamic.

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Probabilistic robot mapping techniques can produce high resolution, accurate maps of large indoor and outdoor environments. However, much less progress has been made towards robots using these maps to perform useful functions such as efficient navigation. This paper describes a pragmatic approach to mapping system development that considers not only the map but also the navigation functionality that the map must provide. We pursue this approach within a bio-inspired mapping context, and use esults from robot experiments in indoor and outdoor environments to demonstrate its validity. The research attempts to stimulate new research directions in the field of robot mapping with a proposal for a new approach that has the potential to lead to more complete mapping and navigation systems.

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This paper presents a new multi-scale place recognition system inspired by the recent discovery of overlapping, multi-scale spatial maps stored in the rodent brain. By training a set of Support Vector Machines to recognize places at varying levels of spatial specificity, we are able to validate spatially specific place recognition hypotheses against broader place recognition hypotheses without sacrificing localization accuracy. We evaluate the system in a range of experiments using cameras mounted on a motorbike and a human in two different environments. At 100% precision, the multiscale approach results in a 56% average improvement in recall rate across both datasets. We analyse the results and then discuss future work that may lead to improvements in both robotic mapping and our understanding of sensory processing and encoding in the mammalian brain.

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This paper presents a novel place recognition algorithm inspired by the recent discovery of overlapping and multi-scale spatial maps in the rodent brain. We mimic this hierarchical framework by training arrays of Support Vector Machines to recognize places at multiple spatial scales. Place match hypotheses are then cross-validated across all spatial scales, a process which combines the spatial specificity of the finest spatial map with the consensus provided by broader mapping scales. Experiments on three real-world datasets including a large robotics benchmark demonstrate that mapping over multiple scales uniformly improves place recognition performance over a single scale approach without sacrificing localization accuracy. We present analysis that illustrates how matching over multiple scales leads to better place recognition performance and discuss several promising areas for future investigation.

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There is an increased interest on the use of UAVs for environmental research and to track bush fire plumes, volcanic plumes or pollutant sources. The aim of this paper is to describe the theory and results of a bio-inspired plume tracking algorithm. A memory based and gradient based approach, were developed and compared. A method for generating sparse plumes was also developed. Results indicate the ability of the algorithms to track plumes in 2D and 3D.

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Several algorithms and techniques widely used in Computer Science have been adapted from, or inspired by, known biological phenomena. This is a consequence of the multidisciplinary background of most early computer scientists. The field has now matured, and permits development of tools and collaborative frameworks which play a vital role in advancing current biomedical research. In this paper, we briefly present examples of the former, and elaborate upon two of the latter, applied to immunological modelling and as a new paradigm in gene expression.

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There is an increased interest on the use of UAVs for environmental research such as tracking bush fires, volcanic eruptions, chemical accidents or pollution sources. The aim of this paper is to describe the theory and results of a bio-inspired plume tracking algorithm. A method for generating sparse plumes in a virtual environment was also developed. Results indicated the ability of the algorithms to track plumes in 2D and 3D. The system has been tested with hardware in the loop (HIL) simulations and in flight using a CO2 gas sensor mounted to a multi-rotor UAV. The UAV is controlled by the plume tracking algorithm running on the ground control station (GCS).

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Scales provide optical disguise, low water drag and mechanical protection to fish, enabling them to survive catastrophic environmental disasters, predators and microorganisms. The unique structures and stacking sequences of fish scales inspired the fabrication of artificial nanostructures with salient optical, interfacial and mechanical properties. Herein, we describe fish-scale bio-inspired multifunctional ZnO nanostructures that have similar morphology and structure to the cycloid scales of the Asian Arowana. These nanostructured coatings feature tunable light refraction and reflection, modulated surface wettability and damage-tolerant mechanical properties. The salient properties of these multifunctional nanostructures are promising for applications in: - (i) optical coatings, sensing or lens arrays for use in reflective displays, packing, advertising and solar energy harvesting; - (ii) self-cleaning surfaces, including anti-smudge, anti-fouling and anti-fogging, and self-sterilizing surfaces, and; - (iii) mechanical/chemical barrier coatings. This study provides a low-cost and large-scale production method for the facile fabrication of these bio-inspired nanostructures and provides new insights for the development of novel functional materials for use in 'smart' structures and applications.

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MgO:Fe3+ (0.1-5 mol%) nanoparticles (NPs) were synthesized via eco-friendly, inexpensive and simple low temperature solution combustion route using Aloe vera gel as fuel. The final products were characterized by SEM, TEM and HRTEM. PXRD data and Rietveld analysis revealed the formation of cubic system. The influence of Fe3+ ion concentration on the structure morphology, UV absorption, PL emission and photocatalytic activity of MgO:Fe3+ NPs were investigated. The yellow emission with CIE chromaticity coordinates (0.44, 0.52) and average correlated color temperature value was found to be 3540 K which corresponds to warm light of NPs. The control of Fe3+. on MgO matrix influences the photocatalytic decolorization of methylene blue (MB) under UV light. The enhanced photocatalytic activity of MgO:Fe3+ (4 mol%) was attributed to dopant concentration, effective crystallite size, textural properties, decreased band gap and capability for reducing the electron hole pair recombination. Further, the trends of inhibitory effect in the presence of different radical scavengers were explored. These findings open up new avenues for the exploration of Fe-doped MgO in eco-friendly water applications and in the process of display devices. (C) 2015 Elsevier B.V. All rights reserved.

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Geckos and many insects have evolved elastically anisotropic adhesive tissues with hierarchical structures that allow these animals not only to adhere robustly to rough surfaces but also to detach easily upon movement. In order to improve Our understanding of the role of elastic anisotropy in reversible adhesion, here we extend the classical JKR model of adhesive contact mechanics to anisotropic materials. In particular, we consider the plane strain problem of a rigid cylinder in non-slipping adhesive contact with a transversely isotropic elastic half space with the axis of symmetry oriented at an angle inclined to the surface. The cylinder is then subjected to an arbitrarily oriented pulling force. The critical force and contact width at pull-off are calculated as a function of the pulling angle. The analysis shows that elastic anisotropy leads to an orientation-dependent adhesion strength which can vary strongly with the direction of pulling. This study may suggest possible mechanisms by which reversible adhesion devices can be designed for engineering applications. (C) 2006 Elsevier Ltd. All rights reserved.

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Biological machines are active devices that are comprised of cells and other biological components. These functional devices are best suited for physiological environments that support cellular function and survival. Biological machines have the potential to revolutionize the engineering of biomedical devices intended for implantation, where the human body can provide the required physiological environment. For engineering such cell-based machines, bio-inspired design can serve as a guiding platform as it provides functionally proven designs that are attainable by living cells. In the present work, a systematic approach was used to tissue engineer one such machine by exclusively using biological building blocks and by employing a bio-inspired design. Valveless impedance pumps were constructed based on the working principles of the embryonic vertebrate heart and by using cells and tissue derived from rats. The function of these tissue-engineered muscular pumps was characterized by exploring their spatiotemporal and flow behavior in order to better understand the capabilities and limitations of cells when used as the engines of biological machines.

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Hierarchical pillar arrays consisting of micrometer-sized polymer setae covered by carbon nanotubes are engineered to deliver the role of spatulae, mimicking the fibrillar adhesive surfaces of geckos. These biomimetic structures conform well and achieve better attachment to rough surfaces, providing a new platform for a variety of applications.

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Hierarchical pillar arrays consisting of micrometer-sized polymer setae covered by carbon nanotubes are engineered to deliver the role of spatulae, mimicking the fibrillar adhesive surfaces of geckos. These biomimetic structures conform well and achieve better attachment to rough surfaces, providing a new platform for a variety of applications. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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THERE ARE MANY different kinds of robots: factory automation systems that weld and assemble car engines; machines that place chocolates into boxes; medical devices that support surgeons in operations requiring high-precision manipulation; cars that drive automatically over long distances; vehicles for planetary exploration; mechanisms for powerline or oil platform inspection; toys and educational toolkits for schools and universities; service robots that deliver meals, clean floors, or mow lawns; and "companion robots" that are real partners for humans and share our daily lives. In a sense, all these robots are inspired by biological systems; it's just a matter of degree. A driverless vehicle imitates animals moving autonomously in the world.© 2012 ACM.