There is a strong current trend in automation towards These often systems that can handle small to medium batch sizes are also often associated with In prototyping situations. Batch numbers High complexity the application described Is for British Airways Heathrow Airport where the number of variations pattern of their meal trays Is large. The batch size the assembly variations Is also extremely variable. Catering at in assembly of each of This thesis describes the justification and design of anautomatic system to assemble these trays whilst retaining the flexibility Inherent In the current manual assembly arrangement.The work examines system layouts. Considering each possibility particularly from the flexibility and potential reliabilityaspects. This leads to the consideration of Industrial robots because of their Inherent flexibility. Consequently the variousconfigurations of robots are examined to assess the suitability of each In a cell arrangement the system which was chosen forIts potential reliability. The work continues by developing the Ideas and techniques of parts feeding to realise the maximumbenefits from a robotic cell system." The thesis describes novel magazining arrangements for handling each of the Items which make. up the tray assembly. Two major developments are described. one for the handling of stackable Items and the other for handling small discrete parts from bulk. Both systems are flexible to accomodate variations In part dimensions and possess ability to be quickly re-configured - to handle completely different parts. The equipment designed and constructed for British Airwaysuses Ideas that could also find use In many similar applications where the components have the same characteristics.

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The work presented in this thesis focuses on the design and testing of a casualty extraction robot intended to stabilize the head and neck of an unresponsive person. The employment of robots in dangerous locales such as combat zones or the site of a natural disaster has the potential to help keep first responders out of harm's way as well as to improve the efficiency of search and rescue teams. After a review of robotic search and rescue platforms the Semi-Autonomous Victim Extraction Robot(SAVER) is introduced. The necessity of a device intended to support the head and cervical spine during transport on a rescue robot is then discussed. The kinematic and dynamic analyses of various candidate differential mechanisms intended for the head stabilization device are described, and the chosen mechanism is demonstrated in a proof-of-concept device. Following testing with a simple PID controller, it was determined an advanced feedback controller with disturbance rejection capabilities was required. Linear Active Disturbance Rejection Control (LADRC) was chosen for its effectiveness in rejecting perturbations and handling modeling uncertainties. The performance the proposed LADRC control scheme was compared with PID in simulation and the results are presented. Finally, a prototype of the device was designed and built to validate the functionality of the subsystem, and the results of the corresponding experimentation are discussed. / M. S. / Robots can help to keep first responders and medics out of dangerous situations by performing the rescue operation themselves or by collaborating with the field medic to make the process quicker and more efficient. The work presented in this thesis begins with a review of state-of-the-art rescue robots followed by the a brief description of the design of a Semi-Autonomous Victim Extraction Robot (SAVER) intended to rescue injured and incapacitated people. After the SAVER system is briefly described, the necessity of a device intended to support the head and cervical spine during transport is discussed. The head stabilization subsystem could also be implemented as a standalone device for use by paramedics to help free up valuable time that would otherwise be spent in manually stabilizing the head and neck of the injured person

Obstacle avoidance is one of the core problems in the field of autonomous navigation. An obstacle avoidance approach is developed for the navigation task of a reconfigurable multi-robot system named STORM, which stands for Self-configurable and Transformable Omni-Directional Robotic Modules. Various mathematical models have been developed in previous work in this field to avoid collision for such robots. In this work, the proposed collision avoidance algorithm is trained via Deep Reinforcement Learning, which enables the robot to learn by itself from its experiences, and then fit a mathematical model by updating the parameters of a neural network. The trained neural network architecture is capable of choosing an action directly based on the input sensor data using the trained neural network architecture. A virtual STORM locomotion module was trained to explore a Gazebo simulation environment without collision, using the proposed collision avoidance strategies based on DRL. The mathematical model of the avoidance algorithm was derived from the simulation and then applied to the prototype of the locomotion module and validated via experiments. Universal software architecture was also designed for the STORM modules. The software architecture has extensible and reusable features that improve the design efficiency and enable parallel development. / Master of Science / In this thesis, an obstacle avoidance approach is described to enable autonomous navigation of a reconfigurable multi-robot system, STORM. The Self-configurable and Transformable Omni-Directional Robotic Modules (STORM) is a novel approach towards heterogeneous swarm robotics. The system has two types of robotic modules, namely the locomotion module and the manipulation module. Each module is able to navigate and perform tasks independently. In addition, the systems are designed to autonomously dock together to perform tasks that the modules individually are unable to accomplish. The proposed obstacle avoidance approach is designed for the modules of STORM, but can be applied to mobile robots in general. In contrast to the existing collision avoidance approaches, the proposed algorithm was trained via deep reinforcement learning (DRL). This enables the robot to learn by itself from its experiences, and then fit a mathematical model by updating the parameters of a neural network. In order to avoid damage to the real robot during the learning phase, a virtual robot was trained inside a Gazebo simulation environment with obstacles. The mathematical model for the collision avoidance strategy obtained through DRL was then validated on a locomotion module prototype of STORM. This thesis also introduces the overall STORM architecture and provides a brief overview of the generalized software architecture designed for the STORM modules. The software architecture has expandable and reusable features that apply well to the swarm architecture while allowing for design efficiency and parallel development.

This thesis explores the field of hand exoskeleton robotic systems with slip detection and its applications. It presents the design and control of the intelligent sensing and force- feedback exoskeleton robotic (iSAFER) glove to create a system capable of intelligent object grasping initiated by detection of the user’s intentions through motion amplification. Using a combination of sensory feedback streams from the glove, the system has the ability to identify and prevent object slippage, as well as adapting grip geometry to the object properties. The slip detection algorithm provides updated inputs to the force controller to prevent an object from being dropped, while only requiring minimal input from a user who may have varying degrees of functionality in their injured hand. This thesis proposes the use of a high dynamic range, low cost conductive elastomer sensor coupled with a negative force derivative trigger that can be leveraged in order to create a controller that can intelligently respond to slip conditions through state machine architecture, and improve the grasping robustness of the exoskeleton. The mechanical and electrical improvements to the previous design, the sensing and force- feedback exoskeleton robotic (SAFER) glove, are described while details of the controller design and the proposed assistive and rehabilitative applications are explained. Experimental results confirming the validity of the proposed system are also presented. In closing, this thesis concludes with topics for future exploration. / Master of Science / Exoskeletons are robotic systems that have rigid external covering, such as links, joints, and/or soft artificial tendons or muscles, for the desired body part to provide support and/or protection. These are typically used to enhance power and strength, provide rehabilitation and assistance, and teleoperate other robots from a distance. While the US Army developed exoskeletons for strengthening purposes, another potential purpose of exoskeletons, which is serving medical needs, such as rehabilitation, attracted a lot of attention. Among numerous illnesses and injuries that may lead to impaired hand functionality, the U.S. Department of Health and Human Services estimated that approximately 470,000 people survive strokes every year in the United States and require continuous rehabilitation to recover their motor functions. Though medical professionals believe that the intensity and duration of rehabilitation is the key for maximizing the rate of recovery, it is often limited due to many reasons, such as cost or difficulty in attending rehabilitation sessions. To augment the availability and quality of rehabilitation, the study of exoskeletons has earned popularity. Beyond the capability of providing simple movements, such as passive rehabilitation, many scientists researched to provide active rehabilitation, which involves active participation from the patients. Furthermore, detecting the patient’s intention to activate the rehabilitation glove became a topic of interest, and many types of sensors were utilized in research. This thesis explores the design and control of the intelligent sensing and force- feedback exoskeleton robotic (iSAFER) glove, which detects the user’s intentions to activate the system through motion amplification. The iSAFER glove performs soft initial grasp until the fingers touch an object. After the object is gently grabbed and lifted, the grasp is autonomously adjusted through slip detection until there is no more slip. To facilitate this idea, a low cost force sensor was created and leveraged to improve the grasping control of the exoskeleton. The mechanical and electrical improvements to the previous design, the sensing and force-feedback exoskeleton robotic (SAFER) glove, are described while details of the controller design and the proposed assistive and rehabilitative applications are explained. Experimental results confirming the validity of the proposed system are also presented. In closing, this thesis concludes with topics for future exploration.

A review of diagnostic methods shows that new techniques are required that quantify system degradation from measured response. Information theory, developed by Claude E. Shannon, involves the quantification of information defining limits in signal processing for reliable data communication. One such technique considers information theory fundamentals forming an analogy between a machine and a communication channel to modify Shannon`s channel capacity concept and apply it to measured machine system response. The technique considers the residual signal (difference between a measured signal induced by faults from a baseline signal) to quantify degradation, perform system health assessment, and diagnose faults. Similar to noise hampering data transmission, mechanical faults hinder power transmission through the system. This residual signal can be viewed as noise within the context of information theory, to permit application of information theory to machines to construct a health measure for assessment of machine health. The goal of this dissertation is to create and study metrics for assessment of machine health. This dissertation explores channel capacity which is grounded and supported by proven theorems of information theory, studies different ways to apply and calculate channel capacity in practical industry settings, and creates methods to assess and pinpoint degradation by applying the channel capacity based measures to signals. Channel capacity is the maximum rate of information that can be sent and received over a channel having a known level of noise. A measured signal from a machine consists of a baseline signal exemplary of health, intrinsic that contaminates all measurements, and signals generated by the faults. Noise, the difference between the measured signal and the baseline signal, consists of intrinsic noise and "fault noise". Separation between fault and intrinsic (embedded in the measurement) noise shows channel capacity calculations for the machine require minimal computational efforts, and calculations are consistent in the presence of intrinsic white noise. Considering the response average or DC component of a signal in the channel capacity calculations adds robustness to diagnostic results. The method successfully predicted robot failures. Important to system health assessment is having a good baseline response as reference. The technique is favorable for industry because it applies to measurement data and calculations are done in the time domain. The technique can be used in semi-conducting industry as a tool monitoring system performance and lowering fab operating cost by extending component use and scheduling maintenance as needed. With a window running average channel capacity the technique is able to locate the fault in time. / text

Η παρούσα διπλωματική εργασία ασχολείται με την πλοήγηση ενός διαφορικού ρομποτικού οχήματος, την εφαρμογή σε αυτό μη γραμμικού ελέγχου που περιλαμβάνει PI ελεγκτές, καθώς και τη μελέτη της ευστάθειάς του. Αρχικά παρουσιάζεται εν συντομία η ιστορική αναδρομή των ρομποτικών συστημάτων από το πρώιμο στάδιό τους έως σήμερα και ακολούθως γίνεται μια προσπάθεια ταξινόμησής τους ανάλογα με τις εφαρμογές τους ή τα τεχνικά χαρακτηριστικά τους. Στο δεύτερο κεφάλαιο γίνεται αναφορά στις βασικότερες συνιστώσες των ρομποτικων συστημάτων όπως είναι τα κινητήρια συστήματα, τα κυκλώματα μετατροπής σήματος, οι ψηφιακοί αισθητήρες και τα συστήματα επικοινωνίας ανθρώπου-ρομποτικού συστήματος. Επιπλέον αναφέρεται εν συντομία η έννοια της μοντελοποίησης συστημάτων, τα μη ολονομικά συστήματα, το κινοδυναμικό μοντέλο του συγκεκριμένου ρομποτικού συστήματος καθώς και η προσομοίωση αυτού στο Matlab / Simulink. Στη συνέχεια αποδεικνύεται ότι το ρομποτικό όχημα, ως ηλεκτρομηχανικό σύστημα, ικανοποιεί την σημαντική ιδιότητα των Euler-Lagrange συστημάτων, την παθητικότητα, που υπό προϋποθέσεις συνεπάγεται την ευστάθειά του. Στο πέμπτο και τελευταίο κεφάλαιο αυτής της εργασίας, γίνεται αρχικά μια εισαγωγή στα συστήματα αυτομάτου ελέγχου και στη συνέχεια παρουσιάζεται η υλοποίηση του ελέγχου , η προσομοίωση και οι αποκρίσεις των μεταβλητών του συγκεκριμένου συστήματος. Η εργασία ολοκληρώνεται με την εξαγωγή κάποιων χρήσιμων συμπερασμάτων. / The present thesis deals with the navigation of a differential robotic vehicle, the application of nonlinear control to this vehicle which includes PI controllers and the study of its stability. At first a short review of the history of robotic systems from their early stage until today is presented. An attempt is also made to classify them according to their application and their technical specifications. In the second part of the thesis, the main components of the robotic systems are mentioned, more specifically motor systems, signal conversion systems, digital sensors, and robot-human system communication. There is also a short reference to the concept of system modelling, non holonomic systems, the kinodynamic model of the specific robotic system as well as its simulation using Matlab / Simulink. It is proven that the robotic vehicle, as an electromechanical system, possesses an important feature of Euler-Lagrange systems, that of passivity which ensures its stability under specific conditions. In the final chapter of the present thesis, an introduction to control systems is attempted and afterwards the simulation and the variables responses of the particular system are presented. Finally, useful conclusions are drawn from the aforementioned analysis.

abstract: Swarms of low-cost, autonomous robots can potentially be used to collectively perform tasks over large domains and long time scales. The design of decentralized, scalable swarm control strategies will enable the development of robotic systems that can execute such tasks with a high degree of parallelism and redundancy, enabling effective operation even in the presence of unknown environmental factors and individual robot failures. Social insect colonies provide a rich source of inspiration for these types of control approaches, since they can perform complex collective tasks under a range of conditions. To validate swarm robotic control strategies, experimental testbeds with large numbers of robots are required; however, existing low-cost robots are specialized and can lack the necessary sensing, navigation, control, and manipulation capabilities. To address these challenges, this thesis presents a formal approach to designing biologically-inspired swarm control strategies for spatially-confined coverage and payload transport tasks, as well as a novel low-cost, customizable robotic platform for testing swarm control approaches. Stochastic control strategies are developed that provably allocate a swarm of robots around the boundaries of multiple regions of interest or payloads to be transported. These strategies account for spatially-dependent effects on the robots' physical distribution and are largely robust to environmental variations. In addition, a control approach based on reinforcement learning is presented for collective payload towing that accommodates robots with heterogeneous maximum speeds. For both types of collective transport tasks, rigorous approaches are developed to identify and translate observed group retrieval behaviors in Novomessor cockerelli ants to swarm robotic control strategies. These strategies can replicate features of ant transport and inherit its properties of robustness to different environments and to varying team compositions. The approaches incorporate dynamical models of the swarm that are amenable to analysis and control techniques, and therefore provide theoretical guarantees on the system's performance. Implementation of these strategies on robotic swarms offers a way for biologists to test hypotheses about the individual-level mechanisms that drive collective behaviors. Finally, this thesis describes Pheeno, a new swarm robotic platform with a three degree-of-freedom manipulator arm, and describes its use in validating a variety of swarm control strategies. / Dissertation/Thesis / Doctoral Dissertation Mechanical Engineering 2017

Aqueous Phase Partitioning has a long history of applications to the analytical characterisation of biomolecules. However process applications have attracted the most interest in biotechnology where it has become widely recognized as a cost-effective technique. The main aim of this work was to explore the proposition that partition in Aqueous Two Phase Systems (ATPS) can be used as an analytical tool to detect protein isoforms and to assess the applicability of the method in clinical assays and for quality control in bioprocessing through examination of several analytical problems. The work also examined the development of automated methods of system preparation and sampling techniques to determine the partition coefficient in ATPS. The study demonstrated that the geometrical form of the phase diagram co-existence curve was of crucial importance since this directly affected the accuracy with which systems of defined Tie Line Length and Mass Ratio could be constructed. The TLL %Bias (accuracy) of a theoretical system range in the PEG1000-(NH4)2SO4 system at shorter TLL (12.2) was in the range +80.6% to -100% while at a longer TLL (53.1) the %Bias (accuracy) was reduced to +0.1% to -1.9%. At the same time the MR %Bias (accuracy) at shorter TLL (12.2) was in the range +59.5% to -21.3% while at the longer TLL (53.1) this was reduced to +2.7% to -2.6%. By contrast in the PEG8000-Dextran500 system the TLL %Bias (accuracy) at shorter TLL (13.1) was in the range +3.7% to -4.12%, while at a longer TLL (31.1) the range was +0.74% to -0.67%. The MR %Bias (accuracy) at the shorter TLL (13.1) was in the range +3.6% to -3% while at the longer TLL (31.1) the range was +1.1% to -1.4%. This illustrated that it is more difficult to work with a high degree of accuracy (e.g. %Bias <5%) close to the critical point in PEG-salt systems than in PEG-dextran systems. Two different approaches were taken to examine analytical phase partitioning. In the first approach the structure of the isoforms of a model protein (ovalbumin) were altered enzymatically. Analytical methods involving Strong Anion-Exchange chromatography were developed and applied to the separation of the ovalbumin isoforms. Removal of the phosphorylated groups (dephosphorylation of ovalbumin) was undertaken using alkaline phosphatase and de-glycosylation was attempted using neuraminidase and Endo-glycosidase F. However, both enzymatic approaches to deglycosylation were unsuccessful. Dephosphorylated isoforms were successfully produced and characterised. After partitioning in ATPS a clear difference was demonstrated between the behaviour of the native and dephosphorylated forms of ovalbumin. The mean % recovery in a PEG-salt ATPS was 99.8% (± 3.59) for the naive protein and 75.6% (± 4.03) for the dephosphorylated form. On the other hand, in a PEG3350-Dextran500 system, where solubility was maintained, a significant difference in the partition coefficient (K) of native and dephosphorylated ovalbumin was found. K for native ovalbumin was 0.85 while the partition coefficient of the dephosphorylated ovalbumin was 0.61. Analysis of covariance (ANCOVA) indicated that the regression coefficients of the respective partition isotherms were significantly different (p value < 0.05). In a second approach to examine analytical phase partitioning, chemical modification of a specific target surface amino acid of another model protein (serum albumin) was used to determine the degree of conjugation of the protein and also to determine its oxidative state. The method examined the reactivity of a free surface thiol to a wide range of labels ( (a) 2-methylsulfonyl-5-phenyl -1,3,4 oxidiazole reagent, (b) N-Ethylmaleimide (NEM) reagent, (c) 5, 5’-dithiobis (2-nitrobenzoate)(DTNB) (Ellman’s reagent), (d) N-pyrenylmaleimide (NPM) reagent, (e) Fluorescein-5-maleimide (F-5-M) Reagent). Only DTNB was found to modify the surface free thiol of serum albumin in a highly specific and quantitative manner. In the course of the development of a partitioning assay for surface free thiols of serum albumin significant oxidative properties were found to be associated with poly(ethylene glycol) PEG solutions and several attempts were made to find an oxidatively safe partitioning system by including antioxidants and by removal of contaminants by freeze drying. PEG3350-Dextran500 was found to provide an oxidatively safe environment for the development of a partitioning assay for the determination of albumin free thiols. A phase partitioning assay system capable of quantitatively resolving protein associated free thiols and low molecular weight thiols from a mixture of the two was developed. Correlation coefficients (R2) for the regression of experimentally determined protein free thiols in the presence of different levels of added LMW free thiol on the known addition of protein ranged from 0.77 to 0.83. The results demonstrated that the assay could quantify and distinguish both types of thiol in a simple two-step procedure.