CABLE-SUSPENDED CPR-D TYPE PARALLEL ROBOT

This paper deals with the analysis and synthesis of a newly selected Cable-suspended Parallel Robot configuration, named CPR-D system. The camera carrier workspace has the shape of a parallelepiped. The CPR-D system has a unique Jacobian matrix that maps the relationship between internal and external coordinates. This geometric relationship is a key solution for the definition of the system kinematic and dynamic models. Because of the CPR-D system complexity, the Lagrange principle of virtual work has been adapted. Two significant Examples have been used for the CPR-D system analysis and validation

From plain visualisation to vibration sensing: using a camera to control the flexibilities in the ITER remote handling equipment

Thermonuclear fusion is expected to play a key role in the energy market during the second half of this century, reaching 20% of the electricity generation by 2100. For many years, fusion scientists and engineers have been developing the various technologies required to build nuclear power stations allowing a sustained fusion reaction. To the maximum possible extent, maintenance operations in fusion reactors are performed manually by qualified workers in full accordance with the "as low as reasonably achievable" (ALARA) principle. However, the option of hands-on maintenance becomes impractical, difficult or simply impossible in many circumstances, such as high biological dose rates. In this case, maintenance tasks will be performed with remote handling (RH) techniques. The International Thermonuclear Experimental Reactor ITER, to be commissioned in southern France around 2025, will be the first fusion experiment producing more power from fusion than energy necessary to heat the plasma. Its main objective is “to demonstrate the scientific and technological feasibility of fusion power for peaceful purposes”. However ITER represents an unequalled challenge in terms of RH system design, since it will be much more demanding and complex than any other remote maintenance system previously designed. The introduction of man-in-the-loop capabilities in the robotic systems designed for ITER maintenance would provide useful assistance during inspection, i.e. by providing the operator the ability and flexibility to locate and examine unplanned targets, or during handling operations, i.e. by making peg-in-hole tasks easier. Unfortunately, most transmission technologies able to withstand the very specific and extreme environmental conditions existing inside a fusion reactor are based on gears, screws, cables and chains, which make the whole system very flexible and subject to vibrations. This effect is further increased as structural parts of the maintenance equipment are generally lightweight and slender structures due to the size and the arduous accessibility to the reactor. Several methodologies aiming at avoiding or limiting the effects of vibrations on RH system performance have been investigated over the past decade. These methods often rely on the use of vibration sensors such as accelerometers. However, reviewing market shows that there is no commercial off-the-shelf (COTS) accelerometer that meets the very specific requirements for vibration sensing in the ITER in-vessel RH equipment (resilience to high total integrated dose, high sensitivity). The customisation and qualification of existing products or investigation of new concepts might be considered. However, these options would inevitably involve high development costs. While an extensive amount of work has been published on the modelling and control of flexible manipulators in the 1980s and 1990s, the possibility to use vision devices to stabilise an oscillating robotic arm has only been considered very recently and this promising solution has not been discussed at length. In parallel, recent developments on machine vision systems in nuclear environment have been very encouraging. Although they do not deal directly with vibration sensing, they open up new prospects in the use of radiation tolerant cameras. This thesis aims to demonstrate that vibration control of remote maintenance equipment operating in harsh environments such as ITER can be achieved without considering any extra sensor besides the embarked rad-hardened cameras that will inevitably be used to provide real-time visual feedback to the operators. In other words it is proposed to consider the radiation-tolerant vision devices as full sensors providing quantitative data that can be processed by the control scheme and not only as plain video feedback providing qualitative information. The work conducted within the present thesis has confirmed that methods based on the tracking of visual features from an unknown environment are effective candidates for the real-time control of vibrations. Oscillations induced at the end effector are estimated by exploiting a simple physical model of the manipulator. Using a camera mounted in an eye-in-hand configuration, this model is adjusted using direct measurement of the tip oscillations with respect to the static environment. The primary contribution of this thesis consists of implementing a markerless tracker to determine the velocity of a tip-mounted camera in an untrimmed environment in order to stabilise an oscillating long-reach robotic arm. In particular, this method implies modifying an existing online interaction matrix estimator to make it self-adjustable and deriving a multimode dynamic model of a flexible rotating beam. An innovative vision-based method using sinusoidal regression to sense low-frequency oscillations is also proposed and tested. Finally, the problem of online estimation of the image capture delay for visual servoing applications with high dynamics is addressed and an original approach based on the concept of cross-correlation is presented and experimentally validated

Geometry linking the art of building and the Universe: Geometric patterns on shells and grid shells

Geometry links the art of building and the physics of space-time. Mathematical breakthroughs in geometry have led to new ways of designing our structures and our ability to visualise and describe the world, phenomena in nature and the universe. However, in contemporary architecture and structural engineering, a more profound understanding of geometry has been forgotten. This thesis aims to resurrect geometry in architecture and engineering in connection with the rapid development of new digital tools for design and production—particularly the connection between the structural action related to the design of the geometrical patterns on shells structures are treated. A brief historical overview of geometry is conducted, and with an emphasis on its applications in architecture in terms of structural design and economic production. Furthermore, the connection to a sustainable building culture from the standpoint of the Davos declaration 2018, calling for a high-quality Baukultur is investigated. The concept of Baukultur (building culture in English) defined in the Davos declaration is related to architectural quality but has a broader meaning as it concerns the final product and the associated processes and its effect in society. Moreover, the concept of craftsmanship and workshop culture is examined, and how it is already present in computer code development and contemporary innovative research cultures combining architectural design and technology. Taking departure from the 18th-century experimental scientist Joseph Plateau and the contemporary artist Andy Goldsworthy, the connection between scientific and artistic research is investigated.Four articles are included; all connected to various ways of architectural applications of geometry in the design process. The first article describes a way to interpret empirically derived brick patterns, specifically the bed joints, using differential geometry. Two methods to apply this in the design processes of new brick vaults are presented. The first is purely geometrical and can be applied on an arbitrary shape with the possibility to apply several patterns; the second is an iterative method of generating a funicular shape and its pattern simultaneously. The second and third paper describes the design and construction process of two different wooden structures built of straight planar laths. Both studies examine the possibilities of using geometry as a link between various parameters in a design process using digital tools to achieve complex forms using simple elements and production methods. The fourth paper examines an appropriate form for a shell, that can balance aesthetics, structural performance and build-ability, with a proposal for the use of surfaces with constant solid angle. In this paper, the surface was generated with a Delaunay triangulation. Thus, future studies would include incorporation of other types of patterns facilitating buildability

THEORETICAL AND NUMERICAL MODELLING OF BIOLOGICALLY INSPIRED COMPOSITE MATERIALS

PhDThe cellular nature of many biological materials, providing them with low density, high strength and high toughness, have fascinated many researchers in the field of botany and structural biology since at least one century. Bamboo, sponges, trabecular bone, tooth and honeybee combs are only few examples of natural materials with cellular architecture. It has been widely recognised that the geometric and mechanical characteristics of the microscopic building blocks play a fundamental role on the behavior observed at the macroscale. Up to date, many efforts have been devoted to the analysis of cellular materials with empty cells to predict the structure-property relations that link the macroscopic properties to the mechanics of their underlying microstructure. Surprisingly, notwithstanding the great advantages of the composite solutions in nature, in the literature a limited number of investigations concern cellular structures having the internal volumes of the cells filled with fluids, fibers or other bulk materials as commonly happens in biology. In particular, a continuum model has not been derived and explicit formulas for the effective elastic constants and constitutive relations are currently not available. To provide a contribution in this limitedly explored research area, this thesis describes the mathematical formulation and modelling technique leading to explicit expressions for the macroscopic elastic constants and stress-strain relations of biologically inspired composite cellular materials. Two examples are included. The first deals with a regular hexagonal architecture inspired by the biological parenchyma tissue. The second concerns a mutable cellular structure, composed by mutable elongated hexagonal cells, inspired by the hygroscopic keel tissue of the ice plant Delosperma nakurense. In both cases, the predicted results are found to be in very good agreement with the available data in the literature. Then, by taking into account the benefits offered by the complex hierarchical organisation of many natural systems, the attention is focused on the potential value of adding structural hierarchy into two-dimensional composite cellular materials having a self-similar hierarchical architecture, in the first case, and different levels with different cell topologies, in the second. In contrast to the traditional cellular materials with empty cells, the analysis reveals that, in the cell-filled configuration, introducing levels of hierarchy leads to an improvement in the specific stiffness. Finally, to offer concrete and relevant tools to engineers for developing future generations of materials with enhanced performance and unusual functionalities, a novel strategy to obtain a honeycomb with mutable cells is proposed. The technique, based on the ancient Japanese art of kirigami, consists in creating a pattern of cuts into a flat sheet of starting material, which is then stretched to give a honeycomb architecture. It emerges a vast range of effective constants that the so-called kirigami honeycomb structures can be designed with, just by changing the value of the applied stretch.Queen Mary University of Londo

Probabilistic Models of Motor Production

N. Bernstein defined the ability of the central neural system (CNS) to control many degrees of freedom of a physical body with all its redundancy and flexibility as the main problem in motor control. He pointed at that man-made mechanisms usually have one, sometimes two degrees of freedom (DOF); when the number of DOF increases further, it becomes prohibitively hard to control them. The brain, however, seems to perform such control effortlessly. He suggested the way the brain might deal with it: when a motor skill is being acquired, the brain artificially limits the degrees of freedoms, leaving only one or two. As the skill level increases, the brain gradually "frees" the previously fixed DOF, applying control when needed and in directions which have to be corrected, eventually arriving to the control scheme where all the DOF are "free". This approach of reducing the dimensionality of motor control remains relevant even today. One the possibles solutions of the Bernstetin's problem is the hypothesis of motor primitives (MPs) - small building blocks that constitute complex movements and facilitite motor learnirng and task completion. Just like in the visual system, having a homogenious hierarchical architecture built of similar computational elements may be beneficial. Studying such a complicated object as brain, it is important to define at which level of details one works and which questions one aims to answer. David Marr suggested three levels of analysis: 1. computational, analysing which problem the system solves; 2. algorithmic, questioning which representation the system uses and which computations it performs; 3. implementational, finding how such computations are performed by neurons in the brain. In this thesis we stay at the first two levels, seeking for the basic representation of motor output. In this work we present a new model of motor primitives that comprises multiple interacting latent dynamical systems, and give it a full Bayesian treatment. Modelling within the Bayesian framework, in my opinion, must become the new standard in hypothesis testing in neuroscience. Only the Bayesian framework gives us guarantees when dealing with the inevitable plethora of hidden variables and uncertainty. The special type of coupling of dynamical systems we proposed, based on the Product of Experts, has many natural interpretations in the Bayesian framework. If the dynamical systems run in parallel, it yields Bayesian cue integration. If they are organized hierarchically due to serial coupling, we get hierarchical priors over the dynamics. If one of the dynamical systems represents sensory state, we arrive to the sensory-motor primitives. The compact representation that follows from the variational treatment allows learning of a motor primitives library. Learned separately, combined motion can be represented as a matrix of coupling values. We performed a set of experiments to compare different models of motor primitives. In a series of 2-alternative forced choice (2AFC) experiments participants were discriminating natural and synthesised movements, thus running a graphics Turing test. When available, Bayesian model score predicted the naturalness of the perceived movements. For simple movements, like walking, Bayesian model comparison and psychophysics tests indicate that one dynamical system is sufficient to describe the data. For more complex movements, like walking and waving, motion can be better represented as a set of coupled dynamical systems. We also experimentally confirmed that Bayesian treatment of model learning on motion data is superior to the simple point estimate of latent parameters. Experiments with non-periodic movements show that they do not benefit from more complex latent dynamics, despite having high kinematic complexity. By having a fully Bayesian models, we could quantitatively disentangle the influence of motion dynamics and pose on the perception of naturalness. We confirmed that rich and correct dynamics is more important than the kinematic representation. There are numerous further directions of research. In the models we devised, for multiple parts, even though the latent dynamics was factorized on a set of interacting systems, the kinematic parts were completely independent. Thus, interaction between the kinematic parts could be mediated only by the latent dynamics interactions. A more flexible model would allow a dense interaction on the kinematic level too. Another important problem relates to the representation of time in Markov chains. Discrete time Markov chains form an approximation to continuous dynamics. As time step is assumed to be fixed, we face with the problem of time step selection. Time is also not a explicit parameter in Markov chains. This also prohibits explicit optimization of time as parameter and reasoning (inference) about it. For example, in optimal control boundary conditions are usually set at exact time points, which is not an ecological scenario, where time is usually a parameter of optimization. Making time an explicit parameter in dynamics may alleviate this

SciTech News Volume 71, No. 1 (2017)

Columns and Reports From the Editor 3 Division News Science-Technology Division 5 Chemistry Division 8 Engineering Division Aerospace Section of the Engineering Division 9 Architecture, Building Engineering, Construction and Design Section of the Engineering Division 11 Reviews Sci-Tech Book News Reviews 12 Advertisements IEEE

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored

Predictive Whole-Body Control of Humanoid Robot Locomotion

Humanoid robots are machines built with an anthropomorphic shape. Despite decades of research into the subject, it is still challenging to tackle the robot locomotion problem from an algorithmic point of view. For example, these machines cannot achieve a constant forward body movement without exploiting contacts with the environment. The reactive forces resulting from the contacts are subject to strong limitations, complicating the design of control laws. As a consequence, the generation of humanoid motions requires to exploit fully the mathematical model of the robot in contact with the environment or to resort to approximations of it. This thesis investigates predictive and optimal control techniques for tackling humanoid robot motion tasks. They generate control input values from the system model and objectives, often transposed as cost function to minimize. In particular, this thesis tackles several aspects of the humanoid robot locomotion problem in a crescendo of complexity. First, we consider the single step push recovery problem. Namely, we aim at maintaining the upright posture with a single step after a strong external disturbance. Second, we generate and stabilize walking motions. In addition, we adopt predictive techniques to perform more dynamic motions, like large step-ups. The above-mentioned applications make use of different simplifications or assumptions to facilitate the tractability of the corresponding motion tasks. Moreover, they consider first the foot placements and only afterward how to maintain balance. We attempt to remove all these simplifications. We model the robot in contact with the environment explicitly, comparing different methods. In addition, we are able to obtain whole-body walking trajectories automatically by only specifying the desired motion velocity and a moving reference on the ground. We exploit the contacts with the walking surface to achieve these objectives while maintaining the robot balanced. Experiments are performed on real and simulated humanoid robots, like the Atlas and the iCub humanoid robots

VI Workshop on Computational Data Analysis and Numerical Methods: Book of Abstracts

The VI Workshop on Computational Data Analysis and Numerical Methods (WCDANM) is going to be held on June 27-29, 2019, in the Department of Mathematics of the University of Beira Interior (UBI), Covilhã, Portugal and it is a unique opportunity to disseminate scientific research related to the areas of Mathematics in general, with particular relevance to the areas of Computational Data Analysis and Numerical Methods in theoretical and/or practical field, using new techniques, giving especial emphasis to applications in Medicine, Biology, Biotechnology, Engineering, Industry, Environmental Sciences, Finance, Insurance, Management and Administration. The meeting will provide a forum for discussion and debate of ideas with interest to the scientific community in general. With this meeting new scientific collaborations among colleagues, namely new collaborations in Masters and PhD projects are expected. The event is open to the entire scientific community (with or without communication/poster)