Tesis sobre el tema "Robotics, Cloud Robotics, Service Robotics, Cloud"
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Yousif, Robert. "A Practical Approach of an Internet of Robotic Things Platform". Thesis, KTH, Mekatronik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-244412.
Texto completoAvhandlingens syfte är att utforma och utveckla en plattform baserat på konceptet Internet of Robotic Things konstruerat av en robotikplattform, en Internet of Things plattform och molntjänster. En Internet of Things plattform är ett globalt nätverk som tillåter många enheter att kommunicera med varandra och överföra data över Internet. En robotikplattform underlättar kontrollen av in/ut mellan mjukvara, mekaniska enheter och elektroniska system. Molntjänster är en gemensam pool av skalbar hårdvara som vanligtvis erbjuds av tredje parts molnleverantörer. En Internet of Robotic Things plattform är en global infrastruktur som underlättar avancerade robotar att interagera över Internet genom en gemensam kommunikationsteknik, en pool av molntjänster som delas av alla uppkopplade robotar som tillåter skalbar lagring och processorkraft.Plattformens huvudkomponenter är robotikplattformen Robot Operating System, Internet of Things plattformen AWS IoT Core och molntjänsterna Amazon DynamoDB och AWS Lambda för lagring och databearbetning.Plattformen evalueras i form av plattformegenskaperna, fördröjningar & funktionstid och visualiseringsförmåga. Plattformen visar lovande resultat i from av fördröjningar mellan två robotar som utbyter data med hjälp av IoT plattformen, där fördröjningarna är begränsade av distanssträckan. Plattformens egenskap att visualisera strömmande data från robotar möjliggör för en operatör att visualisera utvald data från plattformen över internet i realtid.
Chitic, Stefan-Gabriel. "Middleware and programming models for multi-robot systems". Thesis, Lyon, 2018. http://www.theses.fr/2018LYSEI018/document.
Texto completoDespite many years of work in robotics, there is still a lack of established software architecture and middleware for multi-robot systems. A robotic middleware should be designed to abstract the low-level hardware architecture, facilitate communication and integration of new software. This PhD thesis is focusing on middleware for multi-robot system and how we can improve existing frameworks for fleet purposes by adding multi-robot coordination services, development and massive deployment tools. We expect robots to be increasingly useful as they can take advantage of data pushed from other external devices in their decision making instead of just reacting to their local environment (sensors, cooperating robots in a fleet, etc). This thesis first evaluates one of the most recent middleware for mobile robot(s), Robot operating system (ROS) and continues with a state of the art about the commonly used middlewares in robotics. Based on the conclusions, we propose an original contribution in the multi-robot context, called SDfR (Service discovery for Robots), a service discovery mechanism for Robots. The main goal is to propose a mechanism that allows highly mobile robots to keep track of the reachable peers inside a fleet while using an ad-hoc infrastructure. Another objective is to propose a network configuration negotiation protocol. Due to the mobility of robots, classical peer to peer network configuration techniques are not suitable. SDfR is a highly dynamic, adaptive and scalable protocol adapted from Simple Service Discovery Protocol (SSDP). We conduced a set of experiments, using a fleet of Turtlebot robots, to measure and show that the overhead of SDfR is limited. The last part of the thesis focuses on programming model based on timed automata. This type of programming has the benefits of having a model that can be verified and simulated before deploying the application on real robots. In order to enrich and facilitate the development of robotic applications, a new programming model based on timed automata state machines is proposed, called ROSMDB (Robot Operating system Model Driven Behaviour). It provides model checking at development phase and at runtime. This contribution is composed of several components: a graphical interface to create models based on timed automata, an integrated model checker based on UPPAAL and a code skeleton generator. Moreover, a ROS specific framework is proposed to verify the correctness of the execution of the models and to trigger alerts. Finally, we conduct two experiments: one with a fleet of Parrot drones and second with Turtlebots in order to illustrates the proposed model and its ability to check properties
Bruse, Andreas. "Exploiting Cloud Resources For Semantic Scene Understanding On Mobile Robots". Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-169116.
Texto completoModerna mobila robotar har begränsade resurser. Det får inte plats hur mycket hårdvara som helst på roboten och ändå förväntas de utföra arbeten som kräver extremt mycket datorkraft, tillgång till enorm mängd data och samtidigt kommunicera med andra robotar runt omkring sig. Det här examensarbetet utforskar robotik i molnet där komplexa beräk- ningar kan läggas ut i en molntjänst som kan ha tillgång till denna stora mängd datakraft och ha plats för de stora datamängder som behövs. The Ro- bot Operating System, eller ROS, byggs ut för att stödja kommunikation med en molntjänst och det här systemet används sedan för att testa vår lösning på ett så komplext problem som att förstå en omgivning eller miljö på ett seman- tiskt plan. Fördelarna med att använda en molnbaserad lösning används genom att koppla upp sig mot ett objektigenkänningssytem i molnet och för att byg- ga ett objektkategoriseringssystem som förlitar sig på storskaliga datamängder och parallella beräkningsmodeller. Slutligen föreslås en metod för att bygga en tillförlitlig miljöbeskrivning genom att utnyttja semantiska relationer mellan föremål.
Liu, Yuwei. "OpenMP based Action Entropy Active Sensing in Cloud Computing". Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1584809369789769.
Texto completoBhal, Siddharth. "Fog computing for robotics system with adaptive task allocation". Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78723.
Texto completoMaster of Science
Toris, Russell C. "Spatial and Temporal Learning in Robotic Pick-and-Place Domains via Demonstrations and Observations". Digital WPI, 2016. https://digitalcommons.wpi.edu/etd-dissertations/135.
Texto completoNagrath, Vineet. "Software architectures for cloud robotics : the 5 view Hyperactive Transaction Meta-Model (HTM5)". Thesis, Dijon, 2015. http://www.theses.fr/2015DIJOS005/document.
Texto completoSoftware development for cloud connected robotic systems is a complex software engineeringendeavour. These systems are often an amalgamation of one or more robotic platforms, standalonecomputers, mobile devices, server banks, virtual machines, cameras, network elements and ambientintelligence. An agent oriented approach represents robots and other auxiliary systems as agents inthe system.Software development for distributed and diverse systems like cloud robotic systems require specialsoftware modelling processes and tools. Model driven software development for such complexsystems will increase flexibility, reusability, cost effectiveness and overall quality of the end product.The proposed 5-view meta-model has separate meta-models for specifying structure, relationships,trade, system behaviour and hyperactivity in a cloud robotic system. The thesis describes theanatomy of the 5-view Hyperactive Transaction Meta-Model (HTM5) in computation independent,platform independent and platform specific layers. The thesis also describes a domain specificlanguage for computation independent modelling in HTM5.The thesis has presented a complete meta-model for agent oriented cloud robotic systems and hasseveral simulated and real experiment-projects justifying HTM5 as a feasible meta-model
Trowbridge, Michael Aaron. "Autonomous 3D Model Generation of Orbital Debris using Point Cloud Sensors". Thesis, University of Colorado at Boulder, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1558774.
Texto completoA software prototype for autonomous 3D scanning of uncooperatively rotating orbital debris using a point cloud sensor is designed and tested. The software successfully generated 3D models under conditions that simulate some on-orbit orbit challenges including relative motion between observer and target, inconsistent target visibility and a target with more than one plane of symmetry. The model scanning software performed well against an irregular object with one plane of symmetry but was weak against objects with 2 planes of symmetry.
The suitability of point cloud sensors and algorithms for space is examined. Terrestrial Graph SLAM is adapted for an uncooperatively rotating orbital debris scanning scenario. A joint EKF attitude estimate and shape similiarity loop closure heuristic for orbital debris is derived and experimentally tested. The binary Extended Fast Point Feature Histogram (EFPFH) is defined and analyzed as a binary quantization of the floating point EFPFH. Both the binary and floating point EPFH are experimentally tested and compared as part of the joint loop closure heuristic.
Forsman, Mona. "Point cloud densification". Thesis, Umeå universitet, Institutionen för fysik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-39980.
Texto completoWang, Chen. "Connectivity, Security and Integrationfor Cloud Manufacturing". Thesis, KTH, Industriell produktion, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-226522.
Texto completoThis master thesis project aims to connect the industrial robot to the Cloud platform, and evaluate the connectivity and security. To realize better connectivity, security and integration, a modified Cloud Manufacturing System (CRS) architecture is proposed, which is characterized by high modularity, standardization and composability. The architecture’s specific applications in private, public and hybrid cloud are discussed as well. Then, one system architecture with detailed software composition is designed for Cloud Robotics.According to the proposed system architecture, possible security threat sources and corresponding solutions are presented.During the project, Universal Robot 5 (UR5) is utilized as a practical robot instance to develop a communication routine between KTH Cloud and robots. An Application Program Interface (API) written by Python for Universal Robots and the server is established. The API consists of two modularized part, Gateway Agent and Application Package. The Gateway Agent realizes the connection between the Universal Robot 5 (UR5) and the cloud, while theApplication Package can be customized according to specific application and requirements. In this project, three main functions are developed in the Application Package, including data acquisition, data visualization and remote control. Besides, to evaluate connectivity and stability, private robotics cloud system and public robotics cloud system are simulated with KTH Cloud. The hybrid robotics cloud system is discussed as well. Through the results of case studies, the connectivity and integration of Cloud Manufacturing System are verified.
He, Linbo. "Improving 3D Point Cloud Segmentation Using Multimodal Fusion of Projected 2D Imagery Data : Improving 3D Point Cloud Segmentation Using Multimodal Fusion of Projected 2D Imagery Data". Thesis, Linköpings universitet, Datorseende, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157705.
Texto completoTosello, Elisa. "Cognitive Task Planning for Smart Industrial Robots". Doctoral thesis, Università degli studi di Padova, 2016. http://hdl.handle.net/11577/3421918.
Texto completoQuesta ricerca presenta una nuova struttura di Pianificazione Cognitiva delle Attività ideata per Robot Industriali Intelligenti. La struttura rende Cognitivo un manipolatore industriale mobile applicando le tecnologie offerte dal Web Semantico. Viene inoltre introdotto un nuovo algoritmo di Navigazione tra Oggetti Removibili per robot che navigano e manipolano all’interno di una fabbrica. L’obiettivo di Industria 4.0 è quello di creare Fabbriche Intelligenti: fabbriche modulari dotate di sistemi cyber-fisici in grado di customizzare i prodotti pur mantenendo una produzione di massa altamente flessibile. Tali sistemi devono essere in grado di comunicare e cooperare tra loro e con gli agenti umani in tempo reale, attraverso l’Internet delle Cose. Devono sapersi autonomamente ed intelligentemente adattare ai costanti cambiamenti dell’ambiente che li circonda. Devono saper navigare autonomamente all’interno della fabbrica, anche spostando ostacoli che occludono percorsi liberi, ed essere in grado di manipolare questi oggetti anche se visti per la prima volta. Devono essere in grado di imparare dalle loro azioni e da quelle eseguite da altri agenti. La maggior parte dei robot industriali mobili naviga secondo traiettorie generate a priori. Seguono filielettrificatiincorporatinelterrenoolineedipintesulpavimento. Pianificareapriorièfunzionale se l’ambiente è immutevole e i cicli produttivi sono caratterizzati da criticità temporali. E’ preferibile adottare una pianificazione dinamica se, invece, l’area di lavoro ed i compiti assegnati cambiano frequentemente: i robot devono saper navigare autonomamente senza tener conto dei cambiamenti circostanti. Si consideri il comportamento umano: l’uomo ragiona sulla possibilità di spostare ostacolise unaposizione obiettivo nonè raggiungibileose talespostamento puòaccorciare la traiettoria da percorrere. Questo problema viene detto Navigazione tra Oggetti Removibili ed è noto alla robotica di soccorso. Questo lavoro traspone il problema in uno scenario industriale e prova ad affrontare i suoi due obiettivi principali: l’elevata dimensione dello spazio di ricerca ed il trattamento dell’incertezza. L’algoritmo proposto vuole dare priorità di esplorazione alle aree meno esplorate, per questo estende l’algoritmo noto come Kinodynamic Motion Planning by Interior-Exterior Cell Exploration. L’estensione non impone l’elusione degli ostacoli. Assegna ad ogni cella un’importanza che combina lo sforzo necessario per raggiungerla con quello necessario per liberarla da eventuali ostacoli. L’algoritmo risultante è scalabile grazie alla sua indipendenza dalla dimensione della mappa e dal numero, forma e posizione degli ostacoli. Non impone restrizioni sulle azioni da eseguire: ogni oggetto può venir spinto o afferrato. Allo stato attuale, l’algoritmo assume una completa conoscenza del mondo circonstante. L’ambiente è però riconfigurabile di modo che l’algoritmo possa venir facilmente esteso alla risoluzione di problemi di Navigazione tra Oggetti Removibili in ambienti ignoti. L’algoritmo gestisce i feedback dati dai sensori per correggere le incertezze. Solitamente la Robotica separa la risoluzione dei problemi di pianificazione del movimento da quelli di manipolazione. La Navigazione tra Ostacoli Removibili forza il loro trattamento combinato introducendo la necessità di manipolare oggetti diversi, spesso ignoti, durante la navigazione. Adottare prese pre calcolate non fa fronte alla grande quantità e diversità di oggetti esistenti. Questa tesi propone un Framework di Conoscenza Semantica a supporto dell’algoritmo sopra esposto. Essodàairobotlacapacitàdiimparareamanipolareoggettiedisseminareleinformazioni acquisite durante il compimento dei compiti assegnati. Il Framework si compone di un’Ontologia e di un Engine. L’Ontologia estende lo Standard IEEE formulato per Ontologie per la Robotica e l’Automazione andando a definire le manipolazioni apprese e gli oggetti rilevati. È accessibile a qualsiasi robot connesso al Cloud. Può venir considerato I) una raccolta di dati per l’esecuzione efficiente ed affidabile di azioni ripetute; II) un archivio Web per lo scambio di informazioni tra robot e la velocizzazione della fase di apprendimento. Ad ora, non esistono altre ontologie sulla manipolazione che rispettino lo Standard IEEE. Indipendentemente dallo standard, l’Ontologia propostadifferiscedaquelleesistentiperiltipodiinformazionisalvateeperilmodoefficienteincui un agente può accedere a queste informazioni: attraverso un algoritmo di Cascade Hashing molto veloce. L’Engine consente il calcolo e il salvataggio delle manipolazioni non ancora in Ontologia. Si basa su tecniche di Reinforcement Learning che evitano il training massivo su basi di dati a larga scala, favorendo l’interazione uomo-robot. Infatti, viene data ai robot la possibilità di imparare dagli umani attraverso un framework di Apprendimento Robotico da Dimostrazioni. Il sistema finale è flessibile ed adattabile a robot diversi operanti in diversi ambienti industriali. È caratterizzato da una struttura modulare in cui ogni blocco è completamente riutilizzabile. Ogni blocco si basa sul sistema open-source denominato Robot Operating System. Non tutti i controllori industriali sono disegnati per essere compatibili con questa piattaforma. Viene quindi presentato il metodo che è stato adottato per aprire i controllori dei robot industriali e crearne un’interfaccia ROS.
Chleborad, Aaron A. "Grasping unknown novel objects from single view using octant analysis". Thesis, Manhattan, Kan. : Kansas State University, 2010. http://hdl.handle.net/2097/4089.
Texto completoFeydt, Austin Pack. "A Higher-Fidelity Approach to Bridging the Simulation-Reality Gap for 3-D Object Classification". Case Western Reserve University School of Graduate Studies / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1558355175360648.
Texto completoSmith, Michael. "Non-parametric workspace modelling for mobile robots using push broom lasers". Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:50224eb9-73e8-4c8a-b8c5-18360d11e21b.
Texto completoMontelli, Francesco. "Design and Implementation of a Data Platform for Stream Analysis: WeLASER as a Case Study"". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/24928/.
Texto completoBizhuta, Ermal y Dhespina Carhoshi. "Applicability Study of Software Architectures in the Discrete Manufacturing Domain". Thesis, Mälardalens högskola, Inbyggda system, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-44705.
Texto completoPADME
Nyman, Jonas. "Faster Environment Modelling and Integration into Virtual Reality Simulations". Thesis, Högskolan i Skövde, Institutionen för ingenjörsvetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19800.
Texto completoDorotovič, Viktor. "Detekce pohyblivých objektů v prostředí mobilního robota". Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2017. http://www.nusl.cz/ntk/nusl-363889.
Texto completoKonradsson, Albin y Gustav Bohman. "3D Instance Segmentation of Cluttered Scenes : A Comparative Study of 3D Data Representations". Thesis, Linköpings universitet, Datorseende, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177598.
Texto completoLef, Annette. "CAD-Based Pose Estimation - Algorithm Investigation". Thesis, Linköpings universitet, Datorseende, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157776.
Texto completoHamraz, Hamid. "AUTOMATED TREE-LEVEL FOREST QUANTIFICATION USING AIRBORNE LIDAR". UKnowledge, 2018. https://uknowledge.uky.edu/cs_etds/69.
Texto completoSchubert, Stefan. "Optimierter Einsatz eines 3D-Laserscanners zur Point-Cloud-basierten Kartierung und Lokalisierung im In- und Outdoorbereich". Master's thesis, Universitätsbibliothek Chemnitz, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-161415.
Texto completoAl, Hakim Ezeddin. "3D YOLO: End-to-End 3D Object Detection Using Point Clouds". Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-234242.
Texto completoFör att autonoma fordon ska ha en god uppfattning av sin omgivning används moderna sensorer som LiDAR och RADAR. Dessa genererar en stor mängd 3-dimensionella datapunkter som kallas point clouds. Inom utvecklingen av autonoma fordon finns det ett stort behov av att tolka LiDAR-data samt klassificera medtrafikanter. Ett stort antal studier har gjorts om 2D-objektdetektering som analyserar bilder för att upptäcka fordon, men vi är intresserade av 3D-objektdetektering med hjälp av endast LiDAR data. Därför introducerar vi modellen 3D YOLO, som bygger på YOLO (You Only Look Once), som är en av de snabbaste state-of-the-art modellerna inom 2D-objektdetektering för bilder. 3D YOLO tar in ett point cloud och producerar 3D lådor som markerar de olika objekten samt anger objektets kategori. Vi har tränat och evaluerat modellen med den publika träningsdatan KITTI. Våra resultat visar att 3D YOLO är snabbare än dagens state-of-the-art LiDAR-baserade modeller med en hög träffsäkerhet. Detta gör den till en god kandidat för kunna användas av autonoma fordon.
Serra, Sabina. "Deep Learning for Semantic Segmentation of 3D Point Clouds from an Airborne LiDAR". Thesis, Linköpings universitet, Datorseende, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-168367.
Texto completoStålberg, Martin. "Reconstruction of trees from 3D point clouds". Thesis, Uppsala universitet, Avdelningen för systemteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-316833.
Texto completoArlotti, Luca. "Studio di fattibilità tecnico economico per l'automazione di un reparto presse tramite l'applicazione di cobot". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/16184/.
Texto completoTörnblom, Nils. "Underwater 3D Surface Scanning using Structured Light". Thesis, Uppsala universitet, Centrum för bildanalys, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-138205.
Texto completoUhlíř, Jan. "Kalibrace robotického pracoviště". Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-403205.
Texto completoSylvan, Andreas. "Internet of Things in Surface Mount TechnologyElectronics Assembly". Thesis, KTH, Medieteknik och interaktionsdesign, MID, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-209243.
Texto completoI dagsläget upplever tillverkare inom den europeiska ytmonteringsindustrin för elektronikproduktionsomställningar, nedtid för maskiner och processoptimering som sina störstautmaningar. De ser även ett behov av att samla data och dela information mellan maskiner,människor och system som som är delaktiga i tillverkningsprocessen.Sakernas internet, även kallat Internet of Things (IoT), erbjuder teknik som kan göra dettamöjligt. Det här forskningsprojektet besvarar frågan om vilken potential som finns samt vilkautmaningar en implementation av sakernas internet inom europeisk ytmonteringstillverkning avelektronik innebär. Till att börja med introduceras nyckelkoncept inom sakernas internet. Sedandefinieras utgångsläget i elektroniktillverkningsindustrin genom intervjuer med experter.Studien belyser de hinder som ligger i vägen för implementation och föreslår en lösning. Dettainnebär först och främst att datainsamling och delning av data måste uppnås genomanvändning av standardiserade protokoll för sakernas internet ochapplikationsprogrammeringsgränssnitt (APIer). På grund av att elektroniktillverkare inte litar påatt känslig data förblir säker i molnet måste proprietär data separeras från statistisk data. Dettaför att möjliggöra nästa steg som är insamling av så kallad Big Data i en molntjänst. Dettamöjliggör i sin tur för tillverkaren av produktionsmaskiner att erbjuda nya tjänster.
Rosa, João Pedro Carvalho. "CloudRobotics : distributed robotics using cloud computing". Master's thesis, 2016. http://hdl.handle.net/10316/41393.
Texto completoCloud Computing is a paradigm shift in computation that has been gaining traction over the recent years, which is supported by the increasing availability and ubiquity of a reliable wireless connection to the Internet. Cloud Computing enables the access to seemingly unlimited computer resources that are located on an external computer cluster (the Cloud). In contrast, some robots, e.g. drones, have mobility requirements such as maximum size/weight or minimum autonomy, and carrying more onboard computer resources usually means hindering these requirements. This principle can be brought to the field of Robotics hence the name Cloud Robotics. In this case, the goal is to allow robots to perform tasks they would not be able to under normal circumstances and/or to free onboard resources so that more tasks or more complex tasks can be executed at the same time by a mobile robot. There are many existing robotic tasks that can take advantage of massive processing power and storage, such as simultaneous localization and mapping (SLAM), navigation and trajectory planning, image processing, pattern recognition, human-robot interaction and machine learning to name a few. All of these can quickly drain the robot out of its computer resources, especially if some of these tasks are running at the same time. However, in order to access and export data to the Cloud some bandwidth is needed, thus making the system a tradeoff: on the one hand, computation load and storage space is being freed, while on the other hand more strain is being put on the wireless network usage. As wireless connection protocols become more and more powerful, a Cloud-based solution becomes more interesting. This dissertation aims to analyse this tradeoff by adapting two existing multi-robot tasks, working on the Robotic Operating System (ROS), and compare the Cloud-based approach to the traditional one. To validate the capabilities of Cloud-based robotic systems, both simulations and experiments with real robots were conducted. Simulation results show a clear gain in CPU time, while the latter confirms the outcome of the tasks remains the same. Despite the Cloudbased systems, requiring considerably more bandwidth, a modern off-the-shelf Wi-Fi router can provide with enough to support any realistic team of robots. Keywords: Cloud Computing, Cloud Robotics, Wireless Technology, ROS, Computer Resources, Bandwidth.
Ramharuk, Vikash. "Survivable cloud multi-robotics framework for heterogeneous environments". Diss., 2015. http://hdl.handle.net/10500/19698.
Texto completoSchool of Computing
M.Sc. (Computer Science)
Yang, Chung Kai y 楊仲凱. "Developing a remote robotic lab based on cloud services platform". Thesis, 2012. http://ndltd.ncl.edu.tw/handle/67416699091146693491.
Texto completo國立高雄應用科技大學
資訊管理系
100
Currently, many industries during the product development will process experiment in a laboratory. It usually causes dangers to operators. Therefore many schools don’t let students to do the real experiment in order to avoid the dangerous situations. Besides, establish a laboratory must needs huge investments, like money, space. Some schools located in a remote area even can’t afford to pay such huge investments. For the past few years, there are many researches using idea of remote laboratory to solve above problems. Operator can do an experiment at remote laboratory through internet, but those researcher’s system architecture use one-to-one to connect. In other words, user must remember the remote laboratory’s IP address before connect to remote laboratory. It’s hard to work in our real world, cause if there are ten remote laboratories; user needs to remember ten IP address. And past researches didn’t record during an experiment, it wastes resources. Therefore we use the idea of remote laboratory, and combine cloud services platform to be our control center. Operator can know where the laboratories are through connect to this control center. And our system will record during an experiment, student can watch the video to learn how to do an experiment.
Das, Arun. "Scan Registration Using the Normal Distributions Transform and Point Cloud Clustering Techniques". Thesis, 2013. http://hdl.handle.net/10012/7431.
Texto completo"Least-Squares Fit For Points Measured Along Line-Profiles Formed From Line And Arc Segments". Master's thesis, 2013. http://hdl.handle.net/2286/R.I.16444.
Texto completoDissertation/Thesis
M.S. Mechanical Engineering 2013
Fu, Yu y 傅宇. "Fast Homing Techniques for Autonomous Robots using Sparse Image Waypoints and Design of Vision-based Indoor Localization as Cloud Computing Services". Thesis, 2012. http://ndltd.ncl.edu.tw/handle/31413621107397713320.
Texto completo國立臺灣科技大學
電機工程系
100
This thesis first proposes an approach of local visual homing for multi-waypoint robot homing in piecewise linear routes and reduces the navigation time by developing a fast robot homing approach. For a robot with fixed specification, the proposed fast robot homing approach aims to speed up navigation without compromising navigation accuracy. Compared to prior work on local visual homing with SIFT feature matching, the average distance between consecutive waypoints can be lengthened and the robot is allowed to depart at a higher speed from each waypoint. To improve the tolerance to scale differences in a purely SIFT-based approach, log-polar transform is used to find a circular correspondence. A faster but less accurate motion is designed when images are registered by log-polar transform in the beginning of the visual homing. After the robot is relatively close to a targeted waypoint, the more accurate approach of local visual homing is adopted to maintain the navigation accuracy. Experiments demonstrate that not only faster navigation with competitive navigation accuracy can be achieved, but also fewer waypoints are required in order to guide the robot back to its homing place. Besides the fast robot homing approach which is based on a topological map, this thesis also proposes a vision-based metric localization system with cloud computing for indoor environments. Compared to other vision-based localization researches which find the most similar database image to a query image from database images which are captured along a trajectory by using visual vocabulary or general SIFT feature matching approach, the proposed system can find the location of the query image when the query image largely differs in the viewing angle with the closest database image by matching ASIFT features in the query image with the SIFT features in the database images. Two heavy computation processes, the ASIFT feature detection in the query image and the image registration between the query image and database images, are calculated in Hadoop MapReduce computation framework in order to speed up the response to a request of localization service. Experiments not only demonstrate the performance and feasibility of the proposed localization system but also show higher localization correct rate by using the proposed approach than visual vocabulary and general SIFT feature matching approach when the environment is modeled by limited number of database images.
Barnett, Tristan Darrell. "A distributed affective cognitive architecture for cooperative multi-agent learning systems". Thesis, 2012. http://hdl.handle.net/10210/8055.
Texto completoGeneral machine intelligence represents the principal ambition of artificial intelligence research: creating machines that readily adapt to their environment. Machine learning represents the driving force of adaptation in artificial intelligence. However, two pertinent dilemmas emerge from research into machine learning. Firstly, how do intelligent agents learn effectively in real-world environments, in which randomness, perceptual aliasing and dynamics complicate learning algorithms? Secondly, how can intelligent agents exchange knowledge and learn from one another without introducing mathematical anomalies that might impede on the effectiveness of the applied learning algorithms? In a robotic search and rescue scenario, for example, the control system of each robot must learn from its surroundings in a fast-changing and unpredictable environment while at the same time sharing its learned information with others. In well-understood problems, an intelligent agent that is capable of solving task-specific problems will suffice. The challenge behind complex environments comes from fact that agents must solve arbitrary problems (Kaelbling et al. 1996; Ryan 2008). General problem-solving abilities are hence necessary for intelligent agents in complex environments, such as robotic applications. Although specialized machine learning techniques and cognitive hierarchical planning and learning may be a suitable solution for general problem-solving, such techniques have not been extensively explored in the context of cooperative multi-agent learning. In particular, to the knowledge of the author, no cognitive architecture has been designed which can support knowledge-sharing or self-organisation in cooperative multi-agent learning systems. It is therefore social learning in real-world applications that forms the basis of the research presented in this dissertation. This research aims to develop a distributed cognitive architecture for cooperative multi-agent learning in complex environments. The proposed Multi-agent Learning through Distributed Adaptive Contextualization Distributed Cognitive Architecture for Multi-agent Learning (MALDAC) Architecture comprises a self-organising multi-agent system to address the communication constraints that the physical hardware imposes on the system. The individual agents of the system implement their own cognitive learning architecture. The proposed Context-based Adaptive Empathy-deliberation Agent (CAEDA) Architecture investigates the applicability of emotion, ‘consciousness’, embodiment and sociability in cognitive architecture design. Cloud computing is proposed as a method of service delivery for the learning system, in which the MALDAC Architecture governs multiple CAEDA-based agents. An implementation of the proposed architecture is applied to a simulated multi-robot system to best emulate real-world complexities. Analyses indicate favourable results for the cooperative learning capabilities of the proposed MALDAC and CAEDA architectures.
Schubert, Stefan. "Optimierter Einsatz eines 3D-Laserscanners zur Point-Cloud-basierten Kartierung und Lokalisierung im In- und Outdoorbereich". Master's thesis, 2014. https://monarch.qucosa.de/id/qucosa%3A20206.
Texto completo(11211111), Madhu Lekha Guntaka. "IOT BASED LOW-COST PRECISION INDOOR FARMING". Thesis, 2021.
Buscar texto completoThere is a growing demand for indoor farm management systems that can track plant growth, allow automatic control and aid in real-time decision making. Internet of Thing (IoT)-based solutions are being applied to meet these needs and numerous researchers have created prototypes for meeting specific needs using sensors, algorithms, and automations. However, limited studies are available that report on comprehensive large-scale experiments to test various aspects related to availability, scalability and reliability of sensors and actuators used in low-cost indoor farms. The purpose of this study was to develop a low-cost, IoT devices driven indoor farm as a testbed for growing microgreens and other experimental crops. The testbed was designed using off-the-shelf sensors and actuators for conducting research experiments, addressing identified challenges, and utilizing remotely acquired data for developing an intelligent farm management system. The sensors were used for collecting and monitoring electrical conductivity (EC), pH and dissolved oxygen (DO) levels of the nutrient solution, light intensity, environmental variables, and imagery data. The control of light emitting diodes (LEDs), irrigation pumps, and camera modules was carried out using commercially available components. All the sensors and actuators were remotely monitored, controlled, and coordinated using a cloud-based dashboard, Raspberry Pis, and Arduino microcontrollers. To implement a reliable, real-time control of actuators, edge computing was used as it helped in minimizing latency and identifying anomalies.
Decision making about overall system performance and harvesting schedule was accomplished by providing alerts on anomalies in the sensors and actuators and through installation of cameras to predict yield of microgreens, respectively. A split-plot statistical design was used to evaluate the effect of lighting, nutrition solution concentration, seed density, and day of harvest on the growth of microgreens. This study complements and expands past efforts by other researchers on building a low cost IoT-based indoor farm. While the experience with the testbed demonstrates its real-world potential of conducting experimental research, some major lessons were learnt along the way that could be used for future enhancements.