Using nodal coordinates as variables for the dimensional synthesis of mechanisms

The method of the lower deformation energy has been successfully used for the synthesis of mechanisms for quite a while. It has shown to be a versatile, yet powerful method for assisting in the design of mechanisms. Until now, most of the implementations of this method used the dimensions of the mechanism as the synthesis variables, which has some advantages and some drawbacks. For example, the assembly configuration is not taken into account in the optimization process, and this means that the same initial configuration is used when computing the deformed positions in each synthesis point. This translates into a reduction of the total search space. A possible solution to this problem is the use of a set of initial coordinates as variables for the synthesis, which has been successfully applied to other methods. This also has some additional advantages, such as the fact that any generated mechanism can be assembled. Another advantage is that the fixed joint locations are also included in the optimization at no additional cost. But the change from dimensions to initial coordinates means a reformulation of the optimization problem when using derivatives if one wants them to be analytically derived. This paper tackles this reformulation, along with a proper comparison of the use of both alternatives using sequential quadratic programming methods. In order to do so, some examples are developed and studied.The authors wish to thank the Spanish Ministry of Economy and Competitiveness for its support through Grant DPI2013-46329-P and DPI2016-80372-R. Additionally the authors wish to thank the Education Department of the Basque Government for ist support through grant IT947-16

Compliance error compensation technique for parallel robots composed of non-perfect serial chains

The paper presents the compliance errors compensation technique for over-constrained parallel manipulators under external and internal loadings. This technique is based on the non-linear stiffness modeling which is able to take into account the influence of non-perfect geometry of serial chains caused by manufacturing errors. Within the developed technique, the deviation compensation reduces to an adjustment of a target trajectory that is modified in the off-line mode. The advantages and practical significance of the proposed technique are illustrated by an example that deals with groove milling by the Orthoglide manipulator that considers different locations of the workpiece. It is also demonstrated that the impact of the compliance errors and the errors caused by inaccuracy in serial chains cannot be taken into account using the superposition principle.Comment: arXiv admin note: text overlap with arXiv:1204.175

Study and Development of Mechatronic Devices and Machine Learning Schemes for Industrial Applications

Obiettivo del presente progetto di dottorato è lo studio e sviluppo di sistemi meccatronici e di modelli machine learning per macchine operatrici e celle robotizzate al fine di incrementarne le prestazioni operative e gestionali. Le pressanti esigenze del mercato hanno imposto lavorazioni con livelli di accuratezza sempre più elevati, tempi di risposta e di produzione ridotti e a costi contenuti. In questo contesto nasce il progetto di dottorato, focalizzato su applicazioni di lavorazioni meccaniche (e.g. fresatura), che includono sistemi complessi quali, ad esempio, macchine a 5 assi e, tipicamente, robot industriali, il cui utilizzo varia a seconda dell’impiego. Oltre alle specifiche problematiche delle lavorazioni, si deve anche considerare l’interazione macchina-robot per permettere un’efficiente capacità e gestione dell’intero impianto. La complessità di questo scenario può evidenziare sia specifiche problematiche inerenti alle lavorazioni (e.g. vibrazioni) sia inefficienze più generali che riguardano l’impianto produttivo (e.g. asservimento delle macchine con robot, consumo energetico). Vista la vastità della tematica, il progetto si è suddiviso in due parti, lo studio e sviluppo di due specifici dispositivi meccatronici, basati sull’impiego di attuatori piezoelettrici, che puntano principalmente alla compensazione di vibrazioni indotte dal processo di lavorazione, e l’integrazione di robot per l’asservimento di macchine utensili in celle robotizzate, impiegando modelli di machine learning per definire le traiettorie ed i punti di raggiungibilità del robot, al fine di migliorarne l’accuratezza del posizionamento del pezzo in diverse condizioni. In conclusione, la presente tesi vuole proporre soluzioni meccatroniche e di machine learning per incrementare le prestazioni di macchine e sistemi robotizzati convenzionali. I sistemi studiati possono essere integrati in celle robotizzate, focalizzandosi sia su problematiche specifiche delle lavorazioni in macchine operatrici sia su problematiche a livello di impianto robot-macchina. Le ricerche hanno riguardato un’approfondita valutazione dello stato dell’arte, la definizione dei modelli teorici, la progettazione funzionale e l’identificazione delle criticità del design dei prototipi, la realizzazione delle simulazioni e delle prove sperimentali e l’analisi dei risultati.The aim of this Ph.D. project is the study and development of mechatronic systems and machine learning models for machine tools and robotic applications to improve their performances. The industrial demands have imposed an ever-increasing accuracy and efficiency requirement whilst constraining the cost. In this context, this project focuses on machining processes (e.g. milling) that include complex systems such as 5-axes machine tool and industrial robots, employed for various applications. Beside the issues related to the machining process itself, the interaction between the machining centre and the robot must be considered for the complete industrial plant’s improvement. This scenario´s complexity depicts both specific machining problematics (e.g. vibrations) and more general issues related to the complete plant, such as machine tending with an industrial robot and energy consumption. Regarding the immensity of this area, this project is divided in two parts, the study and development of two mechatronic devices, based on piezoelectric stack actuators, for the active vibration control during the machining process, and the robot machine tending within the robotic cell, employing machine learning schemes for the trajectory definition and robot reachability to improve the corresponding positioning accuracy. In conclusion, this thesis aims to provide a set of solutions, based on mechatronic devices and machine learning schemes, to improve the conventional machining centre and the robotic systems performances. The studied systems can be integrated within a robotic cell, focusing on issues related to the specific machining process and to the interaction between robot-machining centre. This research required a thorough study of the state-of-the-art, the formulation of theoretical models, the functional design development, the identification of the critical aspects in the prototype designs, the simulation and experimental campaigns, and the analysis of the obtained results

Steric engineering of metal-halide perovskites with tunable optical band gaps

Owing to their high energy-conversion efficiency and inexpensive fabrication routes, solar cells based on metal-organic halide perovskites have rapidly gained prominence as a disruptive technology. An attractive feature of perovskite absorbers is the possibility of tailoring their properties by changing the elemental composition through the chemical precursors. In this context, rational in silico design represents a powerful tool for mapping the vast materials landscape and accelerating discovery. Here we show that the optical band gap of metal-halide perovskites, a key design parameter for solar cells, strongly correlates with a simple structural feature, the largest metal-halide-metal bond angle. Using this descriptor we suggest continuous tunability of the optical gap from the mid-infrared to the visible. Precise band gap engineering is achieved by controlling the bond angles through the steric size of the molecular cation. Based on these design principles we predict novel low-gap perovskites for optimum photovoltaic efficiency, and we demonstrate the concept of band gap modulation by synthesising and characterising novel mixed-cation perovskites.Comment: This manuscript was submitted for publication on March 6th, 2014. Many of the results presented in this manuscript were presented at the International Conference on Solution processed Semiconductor Solar Cells, held in Oxford, UK, on 10-12 September 2014. The manuscript is 37 pages long and contains 8 figure

Wireless indoor localisation within the 5G internet of radio light

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonNumerous applications can be enhanced by accurate and efficient indoor localisation using wireless sensor networks, however trade-offs often exist between these two parameters. In this thesis, realworld and simulation data is used to examine the hybrid millimeter wave and Visible Light Communications (VLC) architecture of the 5G Internet of Radio Light (IoRL) Horizon 2020 project. Consequently, relevant localisation challenges within Visible Light Positioning (VLP) and asynchronous sampling networks are identified, and more accurate and efficient solutions are developed. Currently, VLP relies strongly on the assumed Lambertian properties of light sources. However, in practice, not all lights are Lambertian. To support the widespread deployment of VLC technology in numerous environments, measurements from non-Lambertian sources are analysed to provide new insights into the limitations of existing VLP techniques. Subsequently, a novel VLP calibration technique is proposed, and results indicate a 59% accuracy improvement against existing methods. This solution enables high accuracy centimetre level VLP to be achieved with non- Lambertian sources. Asynchronous sampling of range-based measurements is known to impact localisation performance negatively. Various Asynchronous Sampling Localisation Techniques (ASLT) exist to mitigate these effects. While effective at improving positioning performance, the exact suitability of such solutions is not evident due to their additional processes, subsequent complexity, and increased costs. As such, extensive simulations are conducted to study the effectiveness of ASLT under variable sampling latencies, sensor measurement noise, and target trajectories. Findings highlight the computational demand of existing ASLT and motivate the development of a novel solution. The proposed Kalman Extrapolated Least Squares (KELS) method achieves optimal localisation performance with a significant energy reduction of over 50% when compared to current leading ASLT. The work in this thesis demonstrates both the capability for high performance VLP from non- Lambertian sources as well as the potential for energy efficient localisation for sequentially sampled range measurements.Horizon 202

Training-free Measures Based on Algorithmic Probability Identify High Nucleosome Occupancy in DNA Sequences

We introduce and study a set of training-free methods of information-theoretic and algorithmic complexity nature applied to DNA sequences to identify their potential capabilities to determine nucleosomal binding sites. We test our measures on well-studied genomic sequences of different sizes drawn from different sources. The measures reveal the known in vivo versus in vitro predictive discrepancies and uncover their potential to pinpoint (high) nucleosome occupancy. We explore different possible signals within and beyond the nucleosome length and find that complexity indices are informative of nucleosome occupancy. We compare against the gold standard (Kaplan model) and find similar and complementary results with the main difference that our sequence complexity approach. For example, for high occupancy, complexity-based scores outperform the Kaplan model for predicting binding representing a significant advancement in predicting the highest nucleosome occupancy following a training-free approach.Comment: 8 pages main text (4 figures), 12 total with Supplementary (1 figure