The cochlea is known to exhibit a nonlinear, mechanical amplification which allows the ear to detect faint sounds, improves frequency discrimination, and broadens the range of sound pressure levels that can be detected. In this work, active artificial hair cells (AHC) are proposed and developed which mimic the nonlinear cochlear amplifier. Active AHCs can be used to transduce sound pressures, fluid flow, accelerations, or another form of dynamic input. These nonlinear sensors consist of piezoelectric cantilever beams which utilize various feedback control laws inspired by the living cochlea. A phenomenological control law is first examined which exhibits similar behavior as the living cochlea. Two sets of physiological models are also examined: one set based on outer hair cell somatic motility and the other set inspired by active hair bundle motility. Compared to passive AHCs, simulation and experimental results for active AHCs show an amplified response due to small stimuli, a sharpened resonance peak, and a compressive nonlinearity between response amplitude and input level. These bio-inspired devices could lead to new sensors with lower thresholds of sound or vibration detection, improved frequency sensitivities, and the ability to detect a wider range of input levels. These bio-inspired, active sensors lay the foundation for a new generation of sensors for acoustic, fluid flow, or vibration sensing. / Ph. D.

The research presented in this thesis includes the development of designs, materials, and fabrication processes and the results of characterization experiments for a meso-scale hydrogel-based lipid bilayer array system. Two design concepts are investigated as methods for forming Droplet Interface Bilayer (DIB) arrays. Both concepts use a base of patterned silver with Ag/AgCl electrodes patterned onto a flat polymer substrate. In one technique, photopolymerizable hydrogel is cured through a mask to form an array of individual hydrogels on top of the patterned electrodes. The other technique introduces a second type of polymer substrate that physically supports an array of hydrogels using a set of microchannels. This second substrate is fitted onto the first to contact the hydrogels to the electrodes. The hydrogels are used to support and shape droplets of water containing phospholipids, which self-assemble at the surface of the droplet when submerged in oil. Two opposing substrates can then be pushed together, and a bilayer will form at the point where each pair of monolayers come into contact. The photopatterning technique is used to produce small arrays of hydrogels on top of a simple electrode pattern. Systems utilizing the microchannel substrate are used to create mesoscale hydrogel arrays of up to 3x3 that maintained a low resistance (~50-150 kΩ) connection to the substrate. Up to three bilayers are formed simultaneously and verified through visual observation and by recording the current response behavior. Arrays of varying sizes and dimensions and with different electrode patterns can be produced quickly and inexpensively using basic laboratory techniques. The designs and fabrication processes for both types of arrays are created with an eye toward future development of similar systems at the microscale. / Master of Science

This research documents the creation and use of an open-loop feed forward control scheme designed to manipulate the DC potential across lipid bilayer membranes in artificial hair cell sensors. Inspired by the human cochlea's non-linear gain phenomenon, whereby the cochlea can increase or decrease the effective gain of the auditory system, this controller is the first step in developing more sophisticated signal processing schemes for use with future bio-inspired artificial hair cell development. This open-loop controller allows for three preset gain mappings to tailor the DC offset in response to an external stimulus. Linear, nonlinear and sigmoidal mappings were created to observe the differences in system response during constant frequency and variable frequency excitation. In constant frequency testing, artificial hair cell sensors were excited at 100 Hz across a range of input intensities to observer current output response during increasing or decreasing excitation levels. Results showed average coherence values above 0.98 for the relationship between current output and fluid velocity, indicating a strong correlation between excitation and measured output. In the bilayer with stereocilia test case, RMS power increased with higher excitation levels but the various control laws did not appear to have any discernible impact on output power. In variable frequency testing, sensors were excited from 0-300 Hz to observe the real time effects of our control law on amplification or attenuation of output current with varying input intensity. Results of the variable frequency excitation could not definitively prove that the varied DC potential had an effect on current output due to excessive capacitive noise, but the controller did provide some encouraging results from its behavior during testing. We observed three distinct DC potential response curves for each mapping, indicating, that with some refinement, we should be able to manipulate output current with user defined gain tunings. / Master of Science

In recent years, the design, fabrication, and control of robotic systems inspired by biology has gained renewed attention due to the potential improvements in efficiency, maneuverability, and adaptability with which animals interact with their environments. Motion studies of biological systems such as humans, fish, insects, birds and bats are often used as a basis for robotic system design. Often, these studies are conducted by recording natural motions of the system of interest using a few high-resolution, high-speed cameras. Such equipment enables the use of standard methods for corresponding features and producing three-dimensional reconstructions of motion. These studies are then interpreted by a designer for kinematic, dynamic, and control systems design of a robotic system. This methodology generates impressive robotic systems which imitate their biological counter parts. However, the equipment used to study motion is expensive and designer interpretation of kinematics data requires substantial time and talent, can be difficult to identify correctly, and often yields kinematic inconsistencies between the robot and biology. To remedy these issues, this dissertation leverages the use of low-cost, low-speed, low-resolution cameras for tracking bat flight and presents a methodology for automatically learning physical geometry which restricts robotic joints to a motion submanifold identified from motion capture data. To this end, we present a spatially recursive state estimator which incorporates inboard state correction for producing accurate state estimates of bat flight. Using these state estimates, we construct a Gaussian process dynamic model (GPDM) of bat flight which is the first nonlinear dimensionality reduction of flapping flight in bats. Additionally, we formulate a novel method for learning robotic joint geometry directly from the experimental observations. To do this, we leverage recent developments in learning theory which derive analytical-empirical potential energy fields for identifying an underlying motion submanifold. We use these energy fields to optimize a compliant structure around a single degree-of-freedom elbow joint and to design rigid structures around spherical joints for an entire bat wing. Validation experiments show that the learned joint geometry restricts the motion of the joints to those observed during experiment. / Ph. D. / In recent years, robots modeled after biological systems have become increasingly prevalent. Such robots are often designed based on motion capture experiments of the animal they aim to imitate. The motion studies are typically conducted using commercial motion capture systems such as ViconTM or OptiTrackTM or a few high-speed, high-resolution cameras such as those marketed by PhotronTM or PhantomTM. These systems allow for automated processing of video sequences into three-dimensional reconstructions of the biological motion using standard image processing and state estimation techniques. The motion data is then used to drive robotic system designs such as the SonyTM AiboTM dog and the Boston Dynamics Atlas humanoid robot. While the motion capture data forms a basis for these impressive robots, the progression from data to robotic system is neither algorithmic nor rigorous and requires substantial interpretation by a human. In contrast, this dissertation presents a novel experimental and computational framework which uses low-speed, low-resolution cameras for capturing the complex motion of bats in flight and introduces a methodology which uses the motion capture data to directly design geometry which restricts the motion of joints to the motions observed in experiment. The advantage of our method is that the designer only needs to specify a general joint geometry such as a ball or pin joint, and geometry which restricts the motion is automatically identified. To do this, we learn an energy field over the set of kinematic configurations observed during experiment. This energy field “pushes” system trajectories towards those experimentally observed trajectories. We then learn compliant or rigid geometry which approximates this energy field to physically restrict the range of motion of the joint. We validate our method by fabricating joint geometry designed using both these approaches and present experiments which confirm that the reachable set of the joint is approximately the same as the set of configurations observed during experiments.

Este trabalho apresenta a concepção, o projeto, o desenvolvimento e a validação experimental de uma plataforma robótica bioinspirada o robô KA\'I yxo com a habilidade de escalar árvores para aplicação em monitoramento ambiental. Tal motivação surgiu da necessidade crescente do estudo e do entendimento de ocorrências naturais pelas consequências envolvidas, muitas vezes trágicas. O monitoramento ambiental em larga escala e a dificuldade de acesso e cobertura de áreas significativas são fatores que indicam a importância e a utilidade de robôs nessas tarefas. O robô KA\'I yxo possui como aplicação primeira uma solução para aquisição de dados de radiação solar, temperatura, umidade e altitude, de maneira que a mesma seja uma ferramenta útil para pesquisadores, aplicação esta identificada como relevante para a pesquisa na área ambiental após visitas ao Instituto Nacional de Pesquisas da Amazônia INPA. O desenvolvimento da plataforma robótica bioinspirada exposto nesta tese apresenta a sua evolução, desde a versão inicial do robô Kamanbaré (seis versões), até a versão atual da plataforma KAI yxo (terceira versão). Para esta última, são expostos em detalhes os modelos mecânico e matemático. No modelo mecânico, a importante questão da mobilidade é considerada. O modelo matemático construído compreende a cinemática direta, a cinemática inversa, a definição da andadura e a dinâmica do robô. O texto contém também uma apresentação detalhada das arquiteturas de controle, de software e de hardware. A utilização de Geradores Centrais de Padrões (CPGs) é justificada e discutida em detalhes. O ajuste dos parâmetros da CPG é realizado por meio de um processo de otimização baseado na técnica de Times Assíncronos (A-Teams). Resultados experimentais obtidos com a plataforma robótica são apresentados e discutidos. / This work presents the conception, design, development and experimental validation of a bioinspired robotics platform the robot KA\'I yxo with the ability to climb trees for use in environmental monitoring. Such motivation arose from the growing need of studying and understanding the consequences of natural occurrences involved, often tragic. Environmental monitoring in large scale and the difficulty of access and coverage areas are significant factors that indicate the importance and the usefulness of robots in these tasks. As a first application, the robot KA\'I yxo represents a solution for data acquisition from solar radiation, temperature, humidity and altitude, so that it may be a useful tool for researchers. This application was identified as relevant to environmental research after visits to the National Institute of Amazonian Research INPA. The development of the bio-inspired robotics platform exposed in this thesis presents its evolution starting from the initial version of the robot Kamanbaré (six versions) and ending with the current version of KA\'I yxo platform (third version). For the latter, the mechanical and mathematical models are exposed in details. In the mechanical model, the important issue of mobility is considered. The mathematical model constructed comprises the forward kinematics, the inverse kinematics, the definition of the gait and the dynamics of the robot. The text also contains a detailed presentation of the control, software and hardware architectures. The use of Central Pattern Generators (CPGs) is justified and discussed. The tuning of the CPG parameters is performed by an optimization process based on the Asynchronous Teams (ATeams) technique. Experimental results obtained with the robotic platform are presented and discussed.

Este trabalho apresenta a concepção, o projeto, o desenvolvimento e a validação experimental de uma plataforma robótica bioinspirada o robô KA\'I yxo com a habilidade de escalar árvores para aplicação em monitoramento ambiental. Tal motivação surgiu da necessidade crescente do estudo e do entendimento de ocorrências naturais pelas consequências envolvidas, muitas vezes trágicas. O monitoramento ambiental em larga escala e a dificuldade de acesso e cobertura de áreas significativas são fatores que indicam a importância e a utilidade de robôs nessas tarefas. O robô KA\'I yxo possui como aplicação primeira uma solução para aquisição de dados de radiação solar, temperatura, umidade e altitude, de maneira que a mesma seja uma ferramenta útil para pesquisadores, aplicação esta identificada como relevante para a pesquisa na área ambiental após visitas ao Instituto Nacional de Pesquisas da Amazônia INPA. O desenvolvimento da plataforma robótica bioinspirada exposto nesta tese apresenta a sua evolução, desde a versão inicial do robô Kamanbaré (seis versões), até a versão atual da plataforma KAI yxo (terceira versão). Para esta última, são expostos em detalhes os modelos mecânico e matemático. No modelo mecânico, a importante questão da mobilidade é considerada. O modelo matemático construído compreende a cinemática direta, a cinemática inversa, a definição da andadura e a dinâmica do robô. O texto contém também uma apresentação detalhada das arquiteturas de controle, de software e de hardware. A utilização de Geradores Centrais de Padrões (CPGs) é justificada e discutida em detalhes. O ajuste dos parâmetros da CPG é realizado por meio de um processo de otimização baseado na técnica de Times Assíncronos (A-Teams). Resultados experimentais obtidos com a plataforma robótica são apresentados e discutidos. / This work presents the conception, design, development and experimental validation of a bioinspired robotics platform the robot KA\'I yxo with the ability to climb trees for use in environmental monitoring. Such motivation arose from the growing need of studying and understanding the consequences of natural occurrences involved, often tragic. Environmental monitoring in large scale and the difficulty of access and coverage areas are significant factors that indicate the importance and the usefulness of robots in these tasks. As a first application, the robot KA\'I yxo represents a solution for data acquisition from solar radiation, temperature, humidity and altitude, so that it may be a useful tool for researchers. This application was identified as relevant to environmental research after visits to the National Institute of Amazonian Research INPA. The development of the bio-inspired robotics platform exposed in this thesis presents its evolution starting from the initial version of the robot Kamanbaré (six versions) and ending with the current version of KA\'I yxo platform (third version). For the latter, the mechanical and mathematical models are exposed in details. In the mechanical model, the important issue of mobility is considered. The mathematical model constructed comprises the forward kinematics, the inverse kinematics, the definition of the gait and the dynamics of the robot. The text also contains a detailed presentation of the control, software and hardware architectures. The use of Central Pattern Generators (CPGs) is justified and discussed. The tuning of the CPG parameters is performed by an optimization process based on the Asynchronous Teams (ATeams) technique. Experimental results obtained with the robotic platform are presented and discussed.

Forests have as a of late become increasingly plagued with bark beetle infestations as a result of climate change. The damage caused by tree killing bark beetles has within recent years seen a substantial increase. Detecting and removing infested trees at an early stage is an essential part of mitigating the spread of and the damage caused by the beetle. Today, the most common way of early detection is visual detection by forestry personnel. However, this is time consuming with highly variable results. In this thesis a novel approach to tracing the European spruce bark beetle through pheromone detection is investigated. With this approach, the antennae of the beetle were paired with an epitaxial graphene chip in order to create a bioinspired smell sensor. Tests were conducted on the sensor in order to investigate how the resistance changed over the chip as a result of the sensor being exposed to the pheromone 2-methyl-3-buten-2-ol. As a result of the tests, a corelation between exposing the sensor to pheromone and an increase of the resistance over the graphene chip was noted. However, more tests need to be conducted in order to draw any definite conclusions about the efficacy of the sensor in its current form. Additionally there are opportunities to investigate further optimization alternatives regarding the design of the sensor.

Nature uses fibrous surfaces for a wide range of functions such as sensing, adhesion, structural color, and self-cleaning. However, little is known about how fiber properties enable them to self-organize into diverse and complex functional forms. Using polymeric micro/nanofiber arrays with tunable properties as model systems, we demonstrate how the combination of mechanical and surface properties can be harnessed to transform an array of anchored nanofibers into a variety of complex, hierarchically organized dynamic functional surfaces. We show that the delicate balance between fiber elasticity and surface adhesion plays a critical role in determining the shape, chirality, and hierarchy of the assembled structures. We further report a strategy for controlling the long-range order of fiber assemblies by manipulating the shape and movement of the liquid-vapor interface. Our study provides fundamental understanding of the pattern formation by self-organization of bioinspired fibrous surfaces. Moreover, our new strategies offer a foundation for designing a vast assortment of functional surfaces with adhesive, optical, water-repellent, capture and release, and many more capabilities with the structural and dynamic sophistication of their biological counterparts. / Engineering and Applied Sciences

La micro extrusion (ou DIW) est une technique de fabrication additive basée sur le dépôt continu de filaments couche par couche. Utilisée pour l'impression de structures poreuses, le DIW de céramiques denses et résistantes reste un défi. L'avantage du DIW réside dans sa capacité à produire des composites, offrant la possibilité de combiner la mise en forme complexe à un contrôle microstructural et fonctionnel précis de matériaux bioinspirés par exemple.Notre travail se concentre sur l'utilisation de gels de boehmite, un précurseur d'Al2O3, en tant que matrice céramique pour obtenir différentes microstructures. Des légers changements dans la composition des gels conduisent à des microstructures et donc à des propriétés différentes. En combinant la polyvalence microstructurale de ces gels avec une maîtrise rhéologique, on peut imprimer des composites avec des propriétés mécaniques améliorées.L'impression de céramiques denses et résistantes passe par la compréhension des propriétés rhéologiques qui définissent une encre imprimable. Le vieillissement de la boehmite est idéal pour corréler les critères géométriques avec la rhéologie pour fournir un critère universel pour l'imprimabilité. Aussi, l'écoulement à l'intérieur des buses de DIW peut aligner des plaquettes d'alumine pendant l'impression. Ceci fournit à l'objet imprimé une ténacité à la rupture accrue dans la direction souhaitée, avec la possibilité de dévier la propagation de la fracture. Un objet peut ainsi être conçu avec précision, en alternant des couches denses et des couches tenaces pour combiner la complexité de la forme avec l'adaptation du comportement mécanique / Direct Ink Writing is an additive manufacturing technique based on continuous layer-by-layer filament deposition. Mostly used to print porous structures, DIW of dense and strong ceramic objects remains an open challenge. However, the advantage of DIW resides in its ability to print multimaterial objects, offering the possibility to combine complex shaping to precise microstructural and functional control, from bioinspired materials, to novel composite structures.Our work focuses on using boehmite gels for DIW, an Al2O3 precursor, as a ceramic matrix to obtain different microstructures. Very small changes to the gels composition lead to completely different microstructures and hence, functional properties. By combining the microstructural versatility of boehmite gels with an understanding of rheology, we are able to print micro and macrocomposites with enhanced mechanical properties. Printing dense and strong ceramic objects starts with understanding the rheological properties that define a printable ink. Boehmite suspensions were ideal to correlate geometrical criteria with rheology and surface tension effects to provide a universal figure of merit for printability. We take advantage of the flow behavior inside DIW nozzles to align alumina platelets during printing. This provides the printed object with increased fracture toughness in the desired direction, with the ability to deviate the fracture propagation perpendicularly to the printing direction. A single object can thus be precisely designed, alternating between dense, strong layers, and directionally tough, fracture deviating layers, to combine the complexity of the shape with the tailoring of mechanical behavior

abstract: A Microbial fuel cell (MFC) is a bio-inspired carbon-neutral, renewable electrochemical converter to extract electricity from catabolic reaction of micro-organisms. It is a promising technology capable of directly converting the abundant biomass on the planet into electricity and potentially alleviate the emerging global warming and energy crisis. The current and power density of MFCs are low compared with conventional energy conversion techniques. Since its debut in 2002, many studies have been performed by adopting a variety of new configurations and structures to improve the power density. The reported maximum areal and volumetric power densities range from 19 mW/m2 to 1.57 W/m2 and from 6.3 W/m3 to 392 W/m3, respectively, which are still low compared with conventional energy conversion techniques. In this dissertation, the impact of scaling effect on the performance of MFCs are investigated, and it is found that by scaling down the characteristic length of MFCs, the surface area to volume ratio increases and the current and power density improves. As a result, a miniaturized MFC fabricated by Micro-Electro-Mechanical System(MEMS) technology with gold anode is presented in this dissertation, which demonstrate a high power density of 3300 W/m3. The performance of the MEMS MFC is further improved by adopting anodes with higher surface area to volume ratio, such as carbon nanotube (CNT) and graphene based anodes, and the maximum power density is further improved to a record high power density of 11220 W/m3. A novel supercapacitor by regulating the respiration of the bacteria is also presented, and a high power density of 531.2 A/m2 (1,060,000 A/m3) and 197.5 W/m2 (395,000 W/m3), respectively, are marked, which are one to two orders of magnitude higher than any previously reported microbial electrochemical techniques. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2016