5 resultados para Software integration

em AMS Tesi di Laurea - Alm@DL - Università di Bologna


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An industrial manipulator equipped with an automatic clay extruder is used to realize a machine that can manufacture additively clay objects. The desired geometries are designed by means of a 3D modeling software and then sliced in a sequence of layers with the same thickness of the extruded clay section. The profiles of each layer are transformed in trajectories for the extruder and therefore for the end-effector of the manipulator. The goal of this thesis is to improve the algorithm for the inverse kinematic resolution and the integration of the routine within the development software that controls the machine (Rhino/Grasshopper). The kinematic model is described by homogeneous transformations, adopting the Denavit-Hartenberg standard convention. The function is implemented in C# and it has been preliminarily tested in Matlab. The outcome of this work is a substantial reduction of the computation time relative to the execution of the algorithm, which is halved.

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Resource management is of paramount importance in network scenarios and it is a long-standing and still open issue. Unfortunately, while technology and innovation continue to evolve, our network infrastructure system has been maintained almost in the same shape for decades and this phenomenon is known as “Internet ossification”. Software-Defined Networking (SDN) is an emerging paradigm in computer networking that allows a logically centralized software program to control the behavior of an entire network. This is done by decoupling the network control logic from the underlying physical routers and switches that forward traffic to the selected destination. One mechanism that allows the control plane to communicate with the data plane is OpenFlow. The network operators could write high-level control programs that specify the behavior of an entire network. Moreover, the centralized control makes it possible to define more specific and complex tasks that could involve many network functionalities, e.g., security, resource management and control, into a single framework. Nowadays, the explosive growth of real time applications that require stringent Quality of Service (QoS) guarantees, brings the network programmers to design network protocols that deliver certain performance guarantees. This thesis exploits the use of SDN in conjunction with OpenFlow to manage differentiating network services with an high QoS. Initially, we define a QoS Management and Orchestration architecture that allows us to manage the network in a modular way. Then, we provide a seamless integration between the architecture and the standard SDN paradigm following the separation between the control and data planes. This work is a first step towards the deployment of our proposal in the University of California, Los Angeles (UCLA) campus network with differentiating services and stringent QoS requirements. We also plan to exploit our solution to manage the handoff between different network technologies, e.g., Wi-Fi and WiMAX. Indeed, the model can be run with different parameters, depending on the communication protocol and can provide optimal results to be implemented on the campus network.

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In recent years, we have witnessed great changes in the industrial environment as a result of the innovations introduced by Industry 4.0, especially in the integration of Internet of Things, Automation and Robotics in the manufacturing field. The project presented in this thesis lies within this innovation context and describes the implementation of an Image Recognition application focused on the automotive field. The project aims at helping the supply chain operator to perform an effective and efficient check of the homologation tags present on vehicles. The user contribution consists in taking a picture of the tag and the application will automatically, exploiting Amazon Web Services, return the result of the control about the correctness of the tag, the correct positioning within the vehicle and the presence of faults or defects on the tag. To implement this application we ombined two IoT platforms widely used in industrial field: Amazon Web Services(AWS) and ThingWorx. AWS exploits Convolutional Neural Networks to perform Text Detection and Image Recognition, while PTC ThingWorx manages the user interface and the data manipulation.

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The paper deals with the integration of ROS, in the proprietary environment of the Marchesini Group company, for the control of industrial robotic systems. The basic tools of this open-source software are deeply studied to model a full proprietary Pick and Place manipulator inside it, and to develop custom ROS nodes to calculate trajectories; speaking of which, the URDF format is the standard to represent robots in ROS and the motion planning framework MoveIt offers user-friendly high-level methods. The communication between ROS and the Marchesini control architecture is established using the OPC UA standard; the tasks computed are transmitted offline to the PLC, supervisor controller of the physical robot, because the performances of the protocol don’t allow any kind of active control by ROS. Once the data are completely stored at the Marchesini side, the industrial PC makes the real robot execute a trajectory computed by MoveIt, so that it replicates the behaviour of the simulated manipulator in Rviz. Multiple experiments are performed to evaluate in detail the potential of ROS in the planning of movements for the company proprietary robots. The project ends with a small study regarding the use of ROS as a simulation platform. First, it is necessary to understand how a robotic application of the company can be reproduced in the Gazebo real world simulator. Then, a ROS node extracts information and examines the simulated robot behaviour, through the subscription to specific topics.

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Il processo di sviluppo di un’applicazione comprende più fasi, ognuna strettamente correlata alle altre. Una delle fasi di questo processo è il rilascio del software, che consiste nel rendere disponibile agli utenti l’applicazione caricandone l’eseguibile su un server, sul quale verrà poi eseguita. Per un’azienda di sviluppo software è particolarmente importante automatizzare e standardizzare il processo di rilascio del software, allo scopo di renderlo più veloce e di diminuire il tempo che intercorre fra una modifica e il momento in cui questa viene effettivamente resa disponibile per gli utenti, ottimizzando infine l’impegno degli sviluppatori. La presente tesi descrive l’implementazione di un sistema di Continuous Integration e Continuous Deliveliry scalabile su una software house con più di 900 dipendenti suddivisi in decine di team, ognuno dei quali ha in carico lo sviluppo di vari software. Le applicazioni realizzate dai team sono generalmente microservizi in esecuzione all’interno di container su piattaforma Kubernetes. Sono state quindi valutate le varie alternative per la realizzazione di questo sistema, analizzandone pro e contro, scegliendo infine GitLab per la parte di Continuous Integration e ArgoCD per la parte di Continuous Deployment. Nei vari capitoli viene quindi analizzata l’infrastruttura esistente e vengono illustrati i vantaggi e svantaggi delle varie soluzioni considerate. Per i due software selezionati viene invece descritto il lavoro svolto, con dettagli sul funzionamento del sistema e la configurazione necessaria per il corretto funzionamento dell’intero processo. La soluzione realizzata effettua build, test, code validation e deploy delle applicazioni seguendo un pattern GitOps, con un repository git contenente la configurazione attuale delle applicazioni, permettendo rollback in caso di problematiche e garantendo un alto livello di sicurezza attraverso il mantenimento dello storico della configurazione e della versione delle applicazioni.