Evolution of Prehension Ability in an Anthropomorphic Neurorobotic Arm

In this paper we show how a simulated anthropomorphic robotic arm controlled by an artificial neural network can develop effective reaching and grasping behaviour through a trial and error process in which the free parameters encode the control rules which regulate the fine-grained interaction between the robot and the environment and variations of the free parameters are retained or discarded on the basis of their effects at the level of the global behaviour exhibited by the robot situated in the environment. The obtained results demonstrate how the proposed methodology allows the robot to produce effective behaviours thanks to its ability to exploit the morphological properties of the robot’s body (i.e. its anthropomorphic shape, the elastic properties of its muscle-like actuators, and the compliance of its actuated joints) and the properties which arise from the physical interaction between the robot and the environment mediated by appropriate control rules

Evolution of Prehension Ability in an Anthropomorphic Neurorobotic Arm

In this paper, we show how a simulated anthropomorphic robotic arm controlled by an artificial neural network can develop effective reaching and grasping behaviour through a trial and error process in which the free parameters encode the control rules which regulate the fine-grained interaction between the robot and the environment and variations of the free parameters are retained or discarded on the basis of their effects at the level of the global behaviour exhibited by the robot situated in the environment. The obtained results demonstrate how the proposed methodology allows the robot to produce effective behaviours thanks to its ability to exploit the morphological properties of the robot's body (i.e. its anthropomorphic shape, the elastic properties of its muscle-like actuators and the compliance of its actuated joints) and the properties which arise from the physical interaction between the robot and the environment mediated by appropriate control rules

Development and Application of the Spherical Harmonic Veto Definer for Gravitational-Wave Transient Search

The rapid analysis of gravitational-wave data is not trivial for many reasons, such as the non-Gaussian non-stationary nature of LIGO detector noise and the lack of exhaustive waveform models. Non-Gaussian non-stationary noise and instrumental artifacts are known as ’glitches’. X-Pipeline Spherical Radiometer (X-SphRad) is a software package designed for performing autonomous searches for un-modelled gravitational- wave bursts. X-SphRad has an approach based on spherical radiometry, that transforms time-series data streams into the spherical harmonic domain. Spherical harmonic coefficients show potential in discriminating glitches from signals. For my Ph.D. thesis, I evaluated and implemented a tool for glitch rejection called Spherical Harmonic Veto Definer (SHaVeD). SHaVeD is a Matlab script that loads spherical harmonic coefficients computed by X-SphRad, and performs statistics that computes a threshold to apply. The threshold is used to identify every glitch’s GPS time and create a cut of one second around it. SHaVeD saves this information in a two-column file where the first column is the GPS starting time of the cut and the second is the final time. X-SphRad can include SHaVeD as a data quality to veto glitches. The tool is tested with X-SphRad and the coherent WaveBurst (cWB) pipeline over the O2 observation run. Results have shown how the inclusion of SHaVeD in the analysis could allow a lowering of some thresholds used in this type of research. Tests show how SHaVeD has reduced the amplitude of the loudest false event by a factor of 3, meaning that it rejected false events in a volume 9 times greater than usual

Evolution of Grasping Behaviour in Anthropomorphic Robotic Arms with Embodied Neural Controllers

The works reported in this thesis focus upon synthesising neural controllers for anthropomorphic robots that are able to manipulate objects through an automatic design process based on artificial evolution. The use of Evolutionary Robotics makes it possible to reduce the characteristics and parameters specified by the designer to a minimum, and the robot’s skills evolve as it interacts with the environment. The primary objective of these experiments is to investigate whether neural controllers that are regulating the state of the motors on the basis of the current and previously experienced sensors (i.e. without relying on an inverse model) can enable the robots to solve such complex tasks. Another objective of these experiments is to investigate whether the Evolutionary Robotics approach can be successfully applied to scenarios that are significantly more complex than those to which it is typically applied (in terms of the complexity of the robot’s morphology, the size of the neural controller, and the complexity of the task). The obtained results indicate that skills such as reaching, grasping, and discriminating among objects can be accomplished without the need to learn precise inverse internal models of the arm/hand structure. This would also support the hypothesis that the human central nervous system (cns) does necessarily have internal models of the limbs (not excluding the fact that it might possess such models for other purposes), but can act by shifting the equilibrium points/cycles of the underlying musculoskeletal system. Consequently, the resulting controllers of such fundamental skills would be less complex. Thus, the learning of more complex behaviours will be easier to design because the underlying controller of the arm/hand structure is less complex. Moreover, the obtained results also show how evolved robots exploit sensory-motor coordination in order to accomplish their tasks

NUCLEATION AND GROWTH BEHAVIOR OF TELLURITE-BASED GLASSES SUITABLE FOR MID-INFRARED APPLICATIONS

Optical fibers transmitting in the 2-5 μm mid-infrared (MIR) spectral region are highly desirable for a variety of military and civilian applications including super-continuum generation, infrared countermeasures (IRCM), and MIR laser sources. These new applications in the mid-infrared require novel optical materials that transmit in this window and can be fabricated into fiber. As tellurite glasses are known to have good transparency in the (NIR) region, tellurite-based glasses are the material of choice for this study due to their high linear and nonlinear refractive index, their low glass transition temperature and the ability to form them into optical fiber. This dissertation summarizes findings on tellurite-based glasses with the composition (90-x)TeO2-10Bi2O3-xZnO with x = 15, 17.5, 20 and 25 that were processed and characterized for their potential application as novel optical fibers. Different techniques were deployed for characterization purposes, which include primarily linear refractive index measurements, structural characterization using Raman spectroscopy, and nucleation and growth behaviors, among others. The viscosity of the glasses was measured using a beam bending and parallel plate viscometers. The kinetics of crystallization of the bulk glasses and fiber with x =20 were studied using a differential scanning analyzer (DTA), a hot stage XRD and an optical microscope. The influence of compositional variation on the physical, thermal and optical properties of the glasses in the TeO2-Bi2O3-ZnO family was established. The parameters such as the thermal properties, activation energy for crystallization, Johnson-Mehl-Avrami exponent, or nucleation and growth domains and rates were determined and were found to depend on the glass composition. We correlated the composition-dependent variation of these parameters to the structure of the glasses via Raman spectroscopy. Key physical, thermal, structural and optical differences were observed and quantified between bulk glasses and their corresponding core and core-clad fibers. Also reported are the processing and characterization of modified tellurite-based glass in the TeO2-Bi2O3-ZnO glass family and efforts to reduce their absorption loss due to residual hydroxyl (OH) content. We discuss the impact of this OH reduction in the tellurite network on the physical, thermal and structural properties as well as nucleation and growth behavior of bulk glass and fiber

Glass and Glass-Ceramic Scaffolds: Manufacturing Methods and the Impact of Crystallization on In-Vitro Dissolution

Synthetic biomaterials mimicking bone morphology have expanded at a tremendous rate. Among all, one stands out: bioactive glass. Bioactive glasses opened the door to a new genre of research into materials able to promote the regeneration of functioning bone tissue. However, despite their ability to promote cell attachment, proliferation and differentiation, these materials are mainly used as granules. However to promote loaded and sustained bone repair, a 3D structure, with open and highly interconnected pores, is desirable. 3D scaffolds are generally produced into green bodies via various techniques. The particles are then bound together via sintering. However, the highly disrupted silica network of the typical bioactive glasses composition leads to crystallization. Therefore, sintering of the most commonly used bioactive glass compositions (i.e. 45S5 and S53P4) leads to partly to fully crystallize bodies. The impact of crystallization on bioactivity still leads to large debate among the scientific community. Does crystallization reduce or suppress the materials bioactivity? Within this chapter, the processing routes for scaffold manufacture are presented, as well as an introduction to the thermal processing of glasses to form glass and glass-ceramics and the consequent effect on bioactivity is discussed