Path planning algorithms for autonomous navigation of a non-holonomic robot in unstructured environments

openPath planning is a crucial aspect of autonomous robot navigation, enabling robots to efficiently and safely navigate through complex environments. This thesis focuses on autonomous navigation for robots in dynamic and uncertain environments. In particular, the project aims to analyze the localization and path planning problems. A fundamental review of the existing literature on path planning algorithms has been carried on. Various factors affecting path planning, such as sensor data fusion, map representation, and motion constraints, are also analyzed. Thanks to the collaboration with E80 Group S.p.A., the project has been developed using ROS (Robot Operating System) on a Clearpath Dingo-O, an indoor mobile robot. To address the challenges posed by unstructured and dynamic environments, ROS follows a combined approach of using a global planner and a local planner. The global planner generates a high-level path, considering the overall environment, while the local planner handles real-time adjustments to avoid moving obstacles and optimize the trajectory. This thesis describes the role of the global planner in a ROS-framework. Performance benchmarking of traditional algorithms like Dijkstra and A*, as well as other techniques, is fundamental in order to understand the limits of these methods. In the end, the Hybrid A* algorithm is introduced as a promising approach for addressing the issues of unstructured environments for autonomous navigation of a non-holonomic robot. The core concepts and implementation details of the algorithm are discussed, emphasizing its ability to efficiently explore continuous state spaces and generate drivable paths.The effectiveness of the proposed path planning algorithms is evaluated through extensive simulations and real-world experiments using the mobile platform. Performance metrics such as path length, execution time, and collision avoidance are analyzed to assess the efficiency and reliability of the algorithms.Path planning is a crucial aspect of autonomous robot navigation, enabling robots to efficiently and safely navigate through complex environments. This thesis focuses on autonomous navigation for robots in dynamic and uncertain environments. In particular, the project aims to analyze the localization and path planning problems. A fundamental review of the existing literature on path planning algorithms has been carried on. Various factors affecting path planning, such as sensor data fusion, map representation, and motion constraints, are also analyzed. Thanks to the collaboration with E80 Group S.p.A., the project has been developed using ROS (Robot Operating System) on a Clearpath Dingo-O, an indoor mobile robot. To address the challenges posed by unstructured and dynamic environments, ROS follows a combined approach of using a global planner and a local planner. The global planner generates a high-level path, considering the overall environment, while the local planner handles real-time adjustments to avoid moving obstacles and optimize the trajectory. This thesis describes the role of the global planner in a ROS-framework. Performance benchmarking of traditional algorithms like Dijkstra and A*, as well as other techniques, is fundamental in order to understand the limits of these methods. In the end, the Hybrid A* algorithm is introduced as a promising approach for addressing the issues of unstructured environments for autonomous navigation of a non-holonomic robot. The core concepts and implementation details of the algorithm are discussed, emphasizing its ability to efficiently explore continuous state spaces and generate drivable paths.The effectiveness of the proposed path planning algorithms is evaluated through extensive simulations and real-world experiments using the mobile platform. Performance metrics such as path length, execution time, and collision avoidance are analyzed to assess the efficiency and reliability of the algorithms

Stellar Mass to Halo Mass Scaling Relation for X-ray Selected Low Mass Galaxy Clusters and Groups out to Redshift z≈1z\approx1

We present the stellar mass-halo mass scaling relation for 46 X-ray selected low-mass clusters or groups detected in the XMM-BCS survey with masses $2\times10^{13}M_{\odot}\lesssim M_{500}\lesssim2.5\times10^{14}M_{\odot}$ at redshift $0.1\le z \le1.02$. The cluster binding masses $M_{500}$ are inferred from the measured X-ray luminosities \Lx, while the stellar masses $M_{\star}$ of the galaxy populations are estimated using near-infrared imaging from the SSDF survey and optical imaging from the BCS survey. With the measured \Lx\ and stellar mass $M_{\star}$, we determine the best fit stellar mass-halo mass relation, accounting for selection effects, measurement uncertainties and the intrinsic scatter in the scaling relation. The resulting mass trend is $M_{\star}\propto M_{500}^{0.69\pm0.15}$, the intrinsic (log-normal) scatter is $\sigma_{\ln M_{\star}|M_{500}}=0.36^{+0.07}_{-0.06}$, and there is no significant redshift trend $M_{\star}\propto (1+z)^{-0.04\pm0.47}$, although the uncertainties are still large. We also examine $M_{\star}$ within a fixed projected radius of $0.5$~Mpc, showing that it provides a cluster binding mass proxy with intrinsic scatter of $\approx93\%$ (1$\sigma$ in $M_{500}$). We compare our $M_{\star}=M_{\star}(M_{500}, z)$ scaling relation from the XMM-BCS clusters with samples of massive, SZE-selected clusters ($M_{500}\approx6\times10^{14}M_{\odot}$) and low mass NIR-selected clusters ($M_{500}\approx10^{14}M_{\odot}$) at redshift $0.6\lesssim z \lesssim1.3$. After correcting for the known mass measurement systematics in the compared samples, we find that the scaling relation is in good agreement with the high redshift samples, suggesting that for both groups and clusters the stellar content of the galaxy populations within $R_{500}$ depends strongly on mass but only weakly on redshift out to $z\approx1$.Comment: 15 pages, 10 figures. Accepted for publication in MNRA

On Information-centric Resiliency and System-level Security in Constrained, Wireless Communication

The Internet of Things (IoT) interconnects many heterogeneous embedded devices either locally between each other, or globally with the Internet. These things are resource-constrained, e.g., powered by battery, and typically communicate via low-power and lossy wireless links. Communication needs to be secured and relies on crypto-operations that are often resource-intensive and in conflict with the device constraints. These challenging operational conditions on the cheapest hardware possible, the unreliable wireless transmission, and the need for protection against common threats of the inter-network, impose severe challenges to IoT networks. In this thesis, we advance the current state of the art in two dimensions. Part I assesses Information-centric networking (ICN) for the IoT, a network paradigm that promises enhanced reliability for data retrieval in constrained edge networks. ICN lacks a lower layer definition, which, however, is the key to enable device sleep cycles and exclusive wireless media access. This part of the thesis designs and evaluates an effective media access strategy for ICN to reduce the energy consumption and wireless interference on constrained IoT nodes. Part II examines the performance of hardware and software crypto-operations, executed on off-the-shelf IoT platforms. A novel system design enables the accessibility and auto-configuration of crypto-hardware through an operating system. One main focus is the generation of random numbers in the IoT. This part of the thesis further designs and evaluates Physical Unclonable Functions (PUFs) to provide novel randomness sources that generate highly unpredictable secrets, on low-cost devices that lack hardware-based security features. This thesis takes a practical view on the constrained IoT and is accompanied by real-world implementations and measurements. We contribute open source software, automation tools, a simulator, and reproducible measurement results from real IoT deployments using off-the-shelf hardware. The large-scale experiments in an open access testbed provide a direct starting point for future research

Planning With Adaptive Dimensionality

Modern systems, such as robots or virtual agents, need to be able to plan their actions in increasingly more complex and larger state-spaces, incorporating many degrees of freedom. However, these high-dimensional planning problems often have low-dimensional representations that describe the problem well throughout most of the state-space. For example, planning for manipulation can be represented by planning a trajectory for the end-effector combined with an inverse kinematics solver through obstacle-free areas of the environment, while planning in the full joint space of the arm is only necessary in cluttered areas. Based on this observation, we have developed the framework for Planning with Adaptive Dimensionality, which makes effective use of state abstraction and dimensionality reduction in order to reduce the size and complexity of the state-space. It iteratively constructs and searches a hybrid state-space consisting of both abstract and non-abstract states. Initially the state-space consists only of abstract states, and regions of non-abstract states are selectively introduced into the state-space in order to maintain the feasibility of the resulting path and the strong theoretical guarantees of the algorithm---completeness and bounds on solution cost sub-optimality. The framework is able to make use of hierarchies of abstractions, as different abstractions can be more effective than others in different parts of the state-space. We have extended the framework to be able to utilize anytime and incremental graph search algorithms. Moreover, we have developed a novel general incremental graph search algorithm---tree-restoring weighted A*, which is able to minimize redundant computation between iterations while efficiently handling changes in the search graph. We have applied our framework to several different domains---navigation for unmanned aerial and ground vehicles, multi-robot collaborative navigation, manipulation and mobile manipulation, and navigation for humanoid robots

Create Web Pages with Web Services

Import 05/08/2014Ústředna Asterisk 12 nabízí širokou škálu možností řízení telefonních hovorů. Tématem této práce je otestovat, jaké jsou možnosti zasílání DTMF kódů s využitím webových služeb. Webová služba je stavěna na základě architektury REST s využitím protokolu HTTP a programovacího jazyka PHP. Uživatelské rozhraní včetně provázání s PHP je zajištěno pomocí technologií javascript a HTML. V práci je také zmíněna technologie java, pro zjištění možností knihovny asterisk-java, která se hojně využívá při budování aplikací k rozšíření funkčnosti ústředny.Asterisk 12 PBX provides a wide range of options for controlling phone calls. The theme of this thesis is to test how is it possible to send DTMF codes with using web services. Web service is built on REST architecture using protocol http and programming language PHP. A user interface including binds to PHP is secured by javascript and HTML technology. The thesis will show also java technology for discovering posibilities of asterisk-java library wich is often used to build applications to extend functionality of pbx.460 - Katedra informatikydobř

Diseño De Red De Comunicación De Datos Para La Institución Educativa Privada Emilio Soyer Cabero Ubicado En El Distrito De Chorrillos, Lima, Perú

El presente trabajo de investigación lleva por título “DISEÑO DE RED DE COMUNICACIÓN DE DATOS PARA LA INSTITUCIÓN EDUCATIVA PRIVADA EMILIO SOYER CABERO UBICADA EN EL DISTRITO DE CHORRILLOS, LIMA, PERÚ”, para optar el título de Ingeniero Electrónico y Telecomunicaciones, presentado por el alumno Jhaset Raúl Ortega Cubas. En primer lugar se aborda la realidad problemática observada relacionada con la importancia y necesidad de diseñar una Red de Comunicación de Datos con el fin de dotar a la Institución Educativa Privada Emilio Soyer Cabero de un sistema de transmisión de información mediante la comunicación de todos los dispositivos de red que ésta maneje para ventaja de los trabajadores, docentes y alumnos. La estructura que hemos seguido en este proyecto se compone de 3 capítulos. El primer capítulo comprende el planteamiento del problema, el segundo capítulo el desarrollo del marco teórico y el tercer capítulo corresponde al desarrollo del diseño

Localization and detection of wireless embeddable structural sensors using an unmanned aerial vehicle in the absence of visual markers

The objective of this thesis is to develop a fully integrated UAV based platform for autonomous collection of data from embedded sensors. Passive (battery-less) embedded sensors provide means for periodic long-term monitoring of civil structures like bridges. However, collection of data from these sensors requires extensive manual effort of locating them. UAVs can automate this process, although localization of these embedded tags in absence of visual markers pose a challenge. A RF (13.56MHz) reader is used to capture data from RF tags wirelessly. Different tag coil sizes are tested to observe effects on read range as well as to characterize the interaction volume between reader and tag. The UAV platform is integrated with the RF reader to autonomously capture data from tags using GPS based localization. Different sensor configurations are tested and characterized to meet the requirements of X,Y,Z localization set by the reader and tag interaction volume. Flight characteristics are also observed for various UAV navigation parameters. Results suggest that by using low-cost RTK GPS unit, the UAV is capable of detecting and localizing RF tags without any visual markers or aides.Electrical and Computer Engineerin

Scheduling language and algorithm development study. Volume 3, phase 2: As-built specifications for the prototype language and module library

Detailed specifications of the prototype language and module library are presented. The user guide to the translator writing system is included

Parallel computing, benchmarking and ATLAS software on ARM

Includes bibliographical references,This thesis explores the use of the ARM architecture in high energy physics computing. ARM processors are predominantly found in smartphones and mobile tablets. Results from benchmarks which were performed on the armv7l architecture are presented. These provide qualitative data as well as confirmation that specialized high energy physics software does run on ARM. This thesis presents the first ever port of the ATLAS software stack to the ARM architecture, as well as the issues that ensued. A new framework, ANA, is introduced which facilitates the compilation of the ATLAS software stack on ARM