10 research outputs found

    Laser-Based Detection and Tracking of Moving Obstacles to Improve Perception of Unmanned Ground Vehicles

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    El objetivo de esta tesis es desarrollar un sistema que mejore la etapa de percepción de vehículos terrestres no tripulados (UGVs) heterogéneos, consiguiendo con ello una navegación robusta en términos de seguridad y ahorro energético en diferentes entornos reales, tanto interiores como exteriores. La percepción debe tratar con obstáculos estáticos y dinámicos empleando sensores heterogéneos, tales como, odometría, sensor de distancia láser (LIDAR), unidad de medida inercial (IMU) y sistema de posicionamiento global (GPS), para obtener la información del entorno con la precisión más alta, permitiendo mejorar las etapas de planificación y evitación de obstáculos. Para conseguir este objetivo, se propone una etapa de mapeado de obstáculos dinámicos (DOMap) que contiene la información de los obstáculos estáticos y dinámicos. La propuesta se basa en una extensión del filtro de ocupación bayesiana (BOF) incluyendo velocidades no discretizadas. La detección de velocidades se obtiene con Flujo Óptico sobre una rejilla de medidas LIDAR discretizadas. Además, se gestionan las oclusiones entre obstáculos y se añade una etapa de seguimiento multi-hipótesis, mejorando la robustez de la propuesta (iDOMap). La propuesta ha sido probada en entornos simulados y reales con diferentes plataformas robóticas, incluyendo plataformas comerciales y la plataforma (PROPINA) desarrollada en esta tesis para mejorar la colaboración entre equipos de humanos y robots dentro del proyecto ABSYNTHE. Finalmente, se han propuesto métodos para calibrar la posición del LIDAR y mejorar la odometría con una IMU

    Robot self-configuration using a physical test harness

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    Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (leaves 101-102).Robot control software packages require a configuration step prior to use. The configuration requires that robot parameters such as the dimensions of the robot, the radius of its wheels, and the location of sensors in body coordinates be provided to the system. Typically, this is accomplished through manual measurement. This thesis describes a method for automating the configuration of essential robot parameters - specifically the size of the wheel radii, the dimensions of the chassis, and the location of the wheelbase with respect to the body frame and compares the results of a preliminary configuration system for the CARMEN robot navigation toolkit to the parameters determined via user measurement. The method is able to estimate the parameters of morphologically analogous robots, for which the shape and sensor types are given, through the use of a physical test harness. The targeted family of robots consists of rectangular, two-wheeled, differential drive robots that are equipped with quadrature phase encoders and current-sensing capabilities. Parameters are discovered by placing the robot in a known physical environment and moving it throughout the enclosed area, performing experiments from which each of the parameters can be calculated. The resulting self-configured parameters are then compared quantitatively to user-measured parameters through several methods including a complete system comparison using the University of Michigan Benchmark (UMBmark) as the standard for comparison. The results demonstrate that while the self-configured parameters do not match user-measured values perfectly, the proposed method remains an adequate technique for automating the configuration of microbot-class robots for use with robotics toolkits.by Javier Alejandro Castro.M.Eng

    Indoor and outdoor rover with Simultaneous Localization And Mapping (SLAM)

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    This work describes the design, development and implementation of a SLAM (Simultaneous Localization And Mapping) consists of two subsystems: low-cost autonomous robot and a ground station where telemetry data and information of the robot are displayed. The goal of a SLAM algorithm is to leave the robot in an unknown environment identify the environment through sensors and extract a map. The self-location of the robot is important in order to locate properly in the space all the sensor data. So the main objective of this project is to develop a low cost SLAM. In this work it will be used hardware for fast prototyping for the proof of concept and so can use it in future teaching. It compares different SLAM algorithms and choosing the most suitable for this system. The chosen algorithm is studied in depth and implemented in the system. Also it is studied one of the common errors in all the terrestrial robots localization: the odometry errors. It is studied these errors and the needed corrections. Then it is studied the hardware components for the construction of an autonomous robot. All parts are analysed individually and it is explained what task realizes each element. Then also is explained the design of the software (both the robot and the ground station) as well as its implementation and functionalities. The software is separated into small pieces to make it more modular and this document explains each of these parts and their functions. Finally, it is shown the results obtained after the development of the system. It has designed a series of tests and analysed the results of each one

    A Novel Approach To Intelligent Navigation Of A Mobile Robot In A Dynamic And Cluttered Indoor Environment

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    The need and rationale for improved solutions to indoor robot navigation is increasingly driven by the influx of domestic and industrial mobile robots into the market. This research has developed and implemented a novel navigation technique for a mobile robot operating in a cluttered and dynamic indoor environment. It divides the indoor navigation problem into three distinct but interrelated parts, namely, localization, mapping and path planning. The localization part has been addressed using dead-reckoning (odometry). A least squares numerical approach has been used to calibrate the odometer parameters to minimize the effect of systematic errors on the performance, and an intermittent resetting technique, which employs RFID tags placed at known locations in the indoor environment in conjunction with door-markers, has been developed and implemented to mitigate the errors remaining after the calibration. A mapping technique that employs a laser measurement sensor as the main exteroceptive sensor has been developed and implemented for building a binary occupancy grid map of the environment. A-r-Star pathfinder, a new path planning algorithm that is capable of high performance both in cluttered and sparse environments, has been developed and implemented. Its properties, challenges, and solutions to those challenges have also been highlighted in this research. An incremental version of the A-r-Star has been developed to handle dynamic environments. Simulation experiments highlighting properties and performance of the individual components have been developed and executed using MATLAB. A prototype world has been built using the WebotsTM robotic prototyping and 3-D simulation software. An integrated version of the system comprising the localization, mapping and path planning techniques has been executed in this prototype workspace to produce validation results

    Cooperative simultaneous localization and mapping framework

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    This research work is a contribution to develop a framework for cooperative simultaneous localization and mapping with multiple heterogeneous mobile robots. The presented research work contributes in two aspects of a team of heterogeneous mobile robots for cooperative map building. First it provides a mathematical framework for cooperative localization and geometric features based map building. Secondly it proposes a software framework for controlling, configuring and managing a team of heterogeneous mobile robots. Since mapping and pose estimation are very closely related to each other, therefore, two novel sensor data fusion techniques are also presented, furthermore, various state of the art localization and mapping techniques and mobile robot software frameworks are discussed for an overview of the current development in this research area. The mathematical cooperative SLAM formulation probabilistically solves the problem of estimating the robots state and the environment features using Kalman filter. The software framework is an effort toward the ongoing standardization process of the cooperative mobile robotics systems. To enhance the efficiency of a cooperative mobile robot system the proposed software framework addresses various issues such as different communication protocol structure for mobile robots, different sets of sensors for mobile robots, sensor data organization from different robots, monitoring and controlling robots from a single interface. The present work can be applied to number of applications in various domains where a priori map of the environment is not available and it is not possible to use global positioning devices to find the accurate position of the mobile robot. Therefore the mobile robot(s) has to rely on building the map of its environment and using the same map to find its position and orientation relative to the environment. The exemplary areas for applying the proposed SLAM technique are Indoor environments such as warehouse management, factory floors for parts assembly line, mapping abandoned tunnels, disaster struck environment which are missing maps, under see pipeline inspection, ocean surveying, military applications, planet exploration and many others. These applications are some of many and are only limited by the imagination.Diese Forschungsarbeit ist ein Beitrag zur Entwicklung eines Framework für kooperatives SLAM mit heterogenen, mobilen Robotern. Die präsentierte Forschungsarbeit trägt in zwei Aspekten in einem Team von heterogenen, mobilen Robotern bei. Erstens stellt es einen mathematischen Framework für kooperative Lokalisierung und geometrisch basierende Kartengenerierung bereit. Zweitens schlägt es einen Softwareframework zur Steuerung, Konfiguration und Management einer Gruppe von heterogenen mobilen Robotern vor. Da Kartenerstellung und Poseschätzung miteinander stark verbunden sind, werden zwei neuartige Techniken zur Sensordatenfusion präsentiert. Weiterhin werden zum Stand der Technik verschiedene Techniken zur Lokalisierung und Kartengenerierung sowie Softwareframeworks für die mobile Robotik diskutiert um einen Überblick über die aktuelle Entwicklung in diesem Forschungsbereich zu geben. Die mathematische Formulierung des SLAM Problems löst das Problem der Roboterzustandsschätzung und der Umgebungmerkmale durch Benutzung eines Kalman filters. Der Softwareframework ist ein Beitrag zum anhaltenden Standardisierungsprozess von kooperativen, mobilen Robotern. Um die Effektivität eines kooperativen mobilen Robotersystems zu verbessern enthält der vorgeschlagene Softwareframework die Möglichkeit die Kommunikationsprotokolle flexibel zu ändern, mit verschiedenen Sensoren zu arbeiten sowie die Möglichkeit die Sensordaten verschieden zu organisieren und verschiedene Roboter von einem Interface aus zu steuern. Die präsentierte Arbeit kann in einer Vielzahl von Applikationen in verschiedenen Domänen benutzt werden, wo eine Karte der Umgebung nicht vorhanden ist und es nicht möglich ist GPS Daten zur präzisen Lokalisierung eines mobilen Roboters zu nutzen. Daher müssen die mobilen Roboter sich auf die selbsterstellte Karte verlassen und die selbe Karte zur Bestimmung von Position und Orientierung relativ zur Umgebung verwenden. Die exemplarischen Anwendungen der vorgeschlagenen SLAM Technik sind Innenraumumgebungen wie Lagermanagement, Fabrikgebäude mit Produktionsstätten, verlassene Tunnel, Katastrophengebiete ohne aktuelle Karte, Inspektion von Unterseepipelines, Ozeanvermessung, Militäranwendungen, Planetenerforschung und viele andere. Diese Anwendungen sind einige von vielen und sind nur durch die Vorstellungskraft limitiert

    Localization Methods for a Mobile Robot in Urban Environments

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    Heterogeneous Robot Swarm – Hardware Design and Implementation

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    Swarm robotics is one the most fascinating, new research areas in the field of robotics, and one of it's grand challenge is the design of swarm robots that are both heterogeneous and self-sufficient. This can be crucial for robots exposed to environments that are unstructured or not easily accessible for a human operator, such as a collapsed building, the deep sea, or the surface of another planet. In Swarm robotics; self-assembly, self-reconfigurability and self-replication are among the most important characteristics as they can add extra capabilities and functionality to the robots besides the robustness, flexibility and scalability. Developing a swarm robot system with heterogeneity and larger behavioral repertoire is addressed in this work. This project is a comprehensive study of the hardware architecture of the homogeneous robot swarm and several problems related to the important aspects of robot's hardware, such as: sensory units, communication among the modules, and hardware components. Most of the hardware platforms used in the swarm robot system are homogeneous and use centralized control architecture for task completion. The hardware architecture is designed and implemented for UB heterogeneous robot swarm with both decentralized and centralized control, depending on the task requirement. Each robot in the UB heterogeneous swarm is equipped with different sensors, actuators, microcontroller and communication modules, which makes them distinct from each other from a hardware point of view. The methodology provides detailed guidelines in designing and implementing the hardware architecture of the heterogeneous UB robot swarm with plug and play approach. We divided the design module into three main categories - sensory modules, locomotion and manipulation, communication and control. We conjecture that the hardware architecture of heterogeneous swarm robots implemented in this work is the most sophisticated and modular design to date

    Behavior-based Control for Service Robots inspired by Human Motion Patterns : a Robotic Shopping Assistant

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    Es wurde, unter Verwendung menschenähnlicher Bewegungsmuster und eines verhaltensbasierten Ansatzes, eine Steuerung für mobile Serviceroboter entwickelt, die Aufgabenplanung, globale und lokale Navigation in dynamischen Umgebungen, sowie die gemeinsame Aufgabenausführung mit einem Benutzer umfasst. Das Verhaltensnetzwerk besteht aus Modulen mit voneinander unabhängigen Aufgaben. Das komplexe Gesamtverhalten des Systems ergibt sich durch die Vereinigung der Einzelverhalten (\u27Emergenz\u27)

    Ein mobiler Serviceroboter zur Automatisierung der Probenahme und des Probenmanagements in einem biotechnologischen Pilotlabor

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    Scherer T. A mobile service robot for automisation of sample taking and sample management in a biotechnological pilot laboratory. Bielefeld (Germany): Bielefeld University; 2004.In biotechnologischen Laboratorien ist die Qualität der typischerweise pharmazeutischen Produkte ein wortwörtlich lebenswichtiges Ziel. Die Qualität der Zellkultivierungen wurde historisch nur durch off-line Messungen von physikalischen Prozessparametern wie pH und pO2 sichergestellt. Biologische Parameter wie die Zelldichte und -viabilität wurden nur off-line gemessen, weil das dazu notwendige Probenmanagement hochkomplizierte Manipulationen und Analysen beinhaltet und deshalb nicht automatisiert werden konnte. Es gibt zwar mehrere automatisierte Geräte, um einem Labortechniker zu assistieren, aber kein System, welches das gesamte Probenmanagement automatisiert. In dieser Arbeit wird ein neuer Typ von Serviceroboter präsentiert, der aus einem auf einer mobilen Plattform montierten Roboterarm besteht und diese Lücke schließt. Dieser Roboter muss eine ganze Reihe von Problemen bewältigen: Er muss seine Position im Labor bestimmen können (Lokalisation), er muss eine kollisionsfreie Bahn zu den beteiligten Geräten finden können (Bahnplanung mit Hindernisvermeidung), er darf bei seinen Bewegungen keine Menschen gefährden oder Laborausrüstung beschädigen (Kollisionsvermeidung), er muss die zu bedienenden Geräte erkennen und ihre Position präzise messen können (Bildverarbeitung), er muss sie bedienen können (Armsteuerung), er muss Objekte greifen können (Greifer und Finger) und er muss sie gefügig handhaben können, um sie nicht zu beschädigen (Kraftregelung). Er muss autonom sein, um nur die allernotwendigste Menge an Benutzereingriffen zu benötigen, und doch durch ein Laborsteuerprogramm kontrollierbar sein, um Eingriffe zu erlauben. Schließlich muss er einfach durch ungeschultes Personal zu warten sein. All diese Aspekte werden von dem in dieser Arbeit präsentierten neuen Robotersystem abgedeckt.In biotechnolgical laboratories, the quality of the typically pharmaceutical product is a literally life-important goal. Historically, the quality of the cell cultivations was ensured by on-line measurements of physical process parameters like pH and pO2 only. Biological parameters like cell density and viability were only measured off-line, because the necessary sample management involves highly complicated manipulations and analyses and could therefore not be automated. Various automated devices to assist a laboratory technician do exist, but so far no system to automate the entire sample management. In this work a novel type of service robot consisting of a robot arm mounted on a mobile platform is presented that closes this gap. This robot has to master a multitude of problems: It must be able to locate its position in the laboratory (localisation), it must be able to find a collision-free path to the involved devices (path planning with obstacle avoidance), it must not endanger humans or damage laboratory equipment while moving (collision avoidance), it must be able to recognize the devices to be manipulated and measure their precise position (computer vision), it must be able to manipulate them (arm control), it must be able to grasp objects (gripper and fingers) and it must be able to handle them with compliance in order to not damage them (force control). It must be autonomous in order to only require the least possible amount of user intervention, and yet controllable by a laboratory control program in order to allow intervention. Finally, it must be easily maintainable by non-expert personell. All these aspects are covered by the novel robot system presented in this thesis
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