Mejoras en el control y sistema de comunicaciones del robot Ballbot-ULL

Este proyecto de fin de carrera forma parte de un proyecto más extenso. Supone la construcción de un robot móvil y autónomo capaz de recibir información del entorno que le rodea y ser capaz de recoger pelotas inmóviles de una pista de tenis.

Integrated visual perception architecture for robotic clothes perception and manipulation

This thesis proposes a generic visual perception architecture for robotic clothes perception and manipulation. This proposed architecture is fully integrated with a stereo vision system and a dual-arm robot and is able to perform a number of autonomous laundering tasks. Clothes perception and manipulation is a novel research topic in robotics and has experienced rapid development in recent years. Compared to the task of perceiving and manipulating rigid objects, clothes perception and manipulation poses a greater challenge. This can be attributed to two reasons: firstly, deformable clothing requires precise (high-acuity) visual perception and dexterous manipulation; secondly, as clothing approximates a non-rigid 2-manifold in 3-space, that can adopt a quasi-infinite configuration space, the potential variability in the appearance of clothing items makes them difficult to understand, identify uniquely, and interact with by machine. From an applications perspective, and as part of EU CloPeMa project, the integrated visual perception architecture refines a pre-existing clothing manipulation pipeline by completing pre-wash clothes (category) sorting (using single-shot or interactive perception for garment categorisation and manipulation) and post-wash dual-arm flattening. To the best of the author’s knowledge, as investigated in this thesis, the autonomous clothing perception and manipulation solutions presented here were first proposed and reported by the author. All of the reported robot demonstrations in this work follow a perception-manipulation method- ology where visual and tactile feedback (in the form of surface wrinkledness captured by the high accuracy depth sensor i.e. CloPeMa stereo head or the predictive confidence modelled by Gaussian Processing) serve as the halting criteria in the flattening and sorting tasks, respectively. From scientific perspective, the proposed visual perception architecture addresses the above challenges by parsing and grouping 3D clothing configurations hierarchically from low-level curvatures, through mid-level surface shape representations (providing topological descriptions and 3D texture representations), to high-level semantic structures and statistical descriptions. A range of visual features such as Shape Index, Surface Topologies Analysis and Local Binary Patterns have been adapted within this work to parse clothing surfaces and textures and several novel features have been devised, including B-Spline Patches with Locality-Constrained Linear coding, and Topology Spatial Distance to describe and quantify generic landmarks (wrinkles and folds). The essence of this proposed architecture comprises 3D generic surface parsing and interpretation, which is critical to underpinning a number of laundering tasks and has the potential to be extended to other rigid and non-rigid object perception and manipulation tasks. The experimental results presented in this thesis demonstrate that: firstly, the proposed grasp- ing approach achieves on-average 84.7% accuracy; secondly, the proposed flattening approach is able to flatten towels, t-shirts and pants (shorts) within 9 iterations on-average; thirdly, the proposed clothes recognition pipeline can recognise clothes categories from highly wrinkled configurations and advances the state-of-the-art by 36% in terms of classification accuracy, achieving an 83.2% true-positive classification rate when discriminating between five categories of clothes; finally the Gaussian Process based interactive perception approach exhibits a substantial improvement over single-shot perception. Accordingly, this thesis has advanced the state-of-the-art of robot clothes perception and manipulation.

Diseño e Implementación de un robot de conocimiento para la extracción de información de los Social Media y Web

Las transformaciones tecnológicas y de información que está experimentando la sociedad, especialmente en la última década, está produciendo un crecimiento exponencial de los datos en todos los ámbitos de la sociedad. Los datos que se generan en los diferentes ámbitos se corresponden con elementos primarios de información que por sí solos son irrelevantes como apoyo a las tomas de decisiones. Para que estos datos puedan ser de utilidad en cualquier proceso de decisión, es preciso que se conviertan en información, es decir, en un conjunto de datos procesados con un significado, para ayudar a crear conocimiento. Estos procesos de transformación de datos en información se componen de diferentes fases como la localización de las fuentes de información, captura, análisis y medición.Este cambio tecnológico y a su vez de la sociedad ha provocado un aumento de las fuentes de información, de manera que cualquier persona, empresas u organización, puede generar información que puede ser relevante para el negocio de las empresas o gobiernos. Localizar estas fuentes, identificar información relevante en la fuente y almacenar la información que generan, la cual puede tener diferentes formatos, es el primer paso de todo el proceso anteriormente descrito, el cual tiene que ser ejecutado de manera correcta ya que el resto de fases dependen de las fuentes y datos recolectados. Para la identificación de información relevante en las fuentes se han creado lo que se denomina, robot de búsqueda, los cuales examinan de manera automática una fuente de información, localizando y recolectando datos que puedan ser de interés.En este trabajo se diseña e implementa un robot de conocimiento junto con los sistemas de captura de información online para fuentes hipertextuales y redes sociales.

De impacto : en milo a go go se armó la grande : sesenta revoluciones por segundo 12

Fondo Margaritainés Restrepo

ROBOT CEMAR: identificación de las capacidades emprendedoras de sus creadores

El XXI Congreso Latinoamericano sobre Espíritu Empresarial, se realizó en la Universidad Icesi los días 6, 7 y 8 de abril de 2011.

Genetic algorithm seeding of idiotypic networks for mobile-robot navigation

Robot-control designers have begun to exploit the properties of the human immune system in order to produce dynamic systems that can adapt to complex, varying, real-world tasks. Jerne’s idiotypic-network theory has proved the most popular artificial-immune-system (AIS) method for incorporation into behaviour-based robotics, since idiotypic selection produces highly adaptive responses. However, previous efforts have mostly focused on evolving the network connections and have often worked with a single, preengineered set of behaviours, limiting variability. This paper describes a method for encoding behaviours as a variable set of attributes, and shows that when the encoding is used with a genetic algorithm (GA), multiple sets of diverse behaviours can develop naturally and rapidly, providing much greater scope for flexible behaviour-selection. The algorithm is tested extensively with a simulated e-puck robot that navigates around a maze by tracking colour. Results show that highly successful behaviour sets can be generated within about 25 minutes, and that much greater diversity can be obtained when multiple autonomous populations are used, rather than a single one.

NUMERICAL SIMULATION STUDY OF VIBRATION MITIGATION EFFECTIVENESS OF TUNED MASS DAMPERS FOR TRAFFIC SIGNAL MAST ARM STRUCTURES

Fatigue damage in the connections of single mast arm signal support structures is one of the primary safety concerns because collapse could result from fatigue induced cracking. This type of cantilever signal support structures typically has very light damping and excessively large wind-induced vibration have been observed. Major changes related to fatigue design were made in the 2001 AASHTO LRFD Specification for Structural Supports for Highway Signs, Luminaries, and Traffic Signals and supplemental damping devices have been shown to be promising in reducing the vibration response and thus fatigue load demand on mast arm signal support structures. The primary objective of this study is to investigate the effectiveness and optimal use of one type of damping devices termed tuned mass damper (TMD) in vibration response mitigation. Three prototype single mast arm signal support structures with 50-ft, 60-ft, and 70-ft respectively are selected for this numerical simulation study. In order to validate the finite element models for subsequent simulation study, analytical modeling of static deflection response of mast arm of the signal support structures was performed and found to be close to the numerical simulation results from beam element based finite element model. A 3-DOF dynamic model was then built using analytically derived stiffness matrix for modal analysis and time history analysis. The free vibration response and forced (harmonic) vibration response of the mast arm structures from the finite element model are observed to be in good agreement with the finite element analysis results. Furthermore, experimental test result from recent free vibration test of a full-scale 50-ft mast arm specimen in the lab is used to verify the prototype structure’s fundamental frequency and viscous damping ratio. After validating the finite element models, a series of parametric study were conducted to examine the trend and determine optimal use of tuned mass damper on the prototype single mast arm signal support structures by varying the following parameters: mass, frequency, viscous damping ratio, and location of TMD. The numerical simulation study results reveal that two parameters that influence most the vibration mitigation effectiveness of TMD on the single mast arm signal pole structures are the TMD frequency and its viscous damping ratio.

Navegación de un robot móvil sobre terreno irregular con contacto de su brazo con el suelo

En esta tesis se aborda el problema de la navegabilidad de robots móviles sobre terrenos irregulares, los cuales poseen diferentes inclinaciones y variedad de obstáculos. Este tema constituye actualmente una línea de investigación activa dirigida al desarrollo de nuevos robots y, adicionalmente, enfocada al desarrollo de estrategias de navegación eficientes y con el mínimo riesgo de inutilización. En primer lugar se desarrolló el robot móvil Lázaro para navegar en este tipo de terrenos, el cual posee un brazo articulado con una rueda como efector final. Esta rueda le permite al brazo mantener un punto de contacto adicional con el suelo que puede ayudar al robot a compensar situaciones de inestabilidad y sobrepasar algunos obstáculos que pudieran presentarse en estos entornos. Posteriormente, se desarrollaron tres medidas cuantitativas que permiten evaluar la navegabilidad de cualquier robot móvil cuando transita sobre terreno irregular. Estas tres medidas son: un índice de estabilidad, el cual evalúa la propensión al vuelco; un índice de direccionamiento, el cual evalúa la disponibilidad del robot para direccionarse y seguir una trayectoria dada y, por último, un índice de deslizamiento, el cual evalúa la propensión del robot a deslizarse hacia abajo cuando se desplaza sobre superficies inclinadas. Finalmente, se definieron un conjunto de maniobras que puede ejecutar Lázaro y que están dirigidas a garantizar la navegación cuando el robot se desplaza sobre superficies inclinadas o cuando debe sobrepasar obstáculos tales como escalones, rampas o zanjas. Todas las estrategias diseñadas se fundamentan en el uso del brazo como herramienta adicional que posee el robot para mejorar su navegabilidad.

TORP: The Open Robot Project A Framework for Module-Based Robots

The development of robots has shown itself as a very complex interdisciplinary research field. The predominant procedure for these developments in the last decades is based on the assumption that each robot is a fully personalized project, with the direct embedding of hardware and software technologies in robot parts with no level of abstraction. Although this methodology has brought countless benefits to the robotics research, on the other hand, it has imposed major drawbacks: (i) the difficulty to reuse hardware and software parts in new robots or new versions; (ii) the difficulty to compare performance of different robots parts; and (iii) the difficulty to adapt development needs-in hardware and software levels-to local groups expertise. Large advances might be reached, for example, if physical parts of a robot could be reused in a different robot constructed with other technologies by other researcher or group. This paper proposes a framework for robots, TORP (The Open Robot Project), that aims to put forward a standardization in all dimensions (electrical, mechanical and computational) of a robot shared development model. This architecture is based on the dissociation between the robot and its parts, and between the robot parts and their technologies. In this paper, the first specification for a TORP family and the first humanoid robot constructed following the TORP specification set are presented, as well as the advances proposed for their improvement.

Motion Planning and Controls with Safety and Temporal Constraints

Motion planning, or trajectory planning, commonly refers to a process of converting high-level task specifications into low-level control commands that can be executed on the system of interest. For different applications, the system will be different. It can be an autonomous vehicle, an Unmanned Aerial Vehicle(UAV), a humanoid robot, or an industrial robotic arm. As human machine interaction is essential in many of these systems, safety is fundamental and crucial. Many of the applications also involve performing a task in an optimal manner within a given time constraint. Therefore, in this thesis, we focus on two aspects of the motion planning problem. One is the verification and synthesis of the safe controls for autonomous ground and air vehicles in collision avoidance scenarios. The other part focuses on the high-level planning for the autonomous vehicles with the timed temporal constraints. In the first aspect of our work, we first propose a verification method to prove the safety and robustness of a path planner and the path following controls based on reachable sets. We demonstrate the method on quadrotor and automobile applications. Secondly, we propose a reachable set based collision avoidance algorithm for UAVs. Instead of the traditional approaches of collision avoidance between trajectories, we propose a collision avoidance scheme based on reachable sets and tubes. We then formulate the problem as a convex optimization problem seeking control set design for the aircraft to avoid collision. We apply our approach to collision avoidance scenarios of quadrotors and fixed-wing aircraft. In the second aspect of our work, we address the high level planning problems with timed temporal logic constraints. Firstly, we present an optimization based method for path planning of a mobile robot subject to timed temporal constraints, in a dynamic environment. Temporal logic (TL) can address very complex task specifications such as safety, coverage, motion sequencing etc. We use metric temporal logic (MTL) to encode the task specifications with timing constraints. We then translate the MTL formulae into mixed integer linear constraints and solve the associated optimization problem using a mixed integer linear program solver. We have applied our approach on several case studies in complex dynamical environments subjected to timed temporal specifications. Secondly, we also present a timed automaton based method for planning under the given timed temporal logic specifications. We use metric interval temporal logic (MITL), a member of the MTL family, to represent the task specification, and provide a constructive way to generate a timed automaton and methods to look for accepting runs on the automaton to find an optimal motion (or path) sequence for the robot to complete the task.

Mimicking the behaviour of idiotypic AIS robot controllers using probabilistic systems

Previous work has shown that robot navigation systems that employ an architecture based upon the idiotypic network theory of the immune system have an advantage over control techniques that rely on reinforcement learning only. This is thought to be a result of intelligent behaviour selection on the part of the idiotypic robot. In this paper an attempt is made to imitate idiotypic dynamics by creating controllers that use reinforcement with a number of different probabilistic schemes to select robot behaviour. The aims are to show that the idiotypic system is not merely performing some kind of periodic random behaviour selection, and to try to gain further insight into the processes that govern the idiotypic mechanism. Trials are carried out using simulated Pioneer robots that undertake navigation exercises. Results show that a scheme that boosts the probability of selecting highly-ranked alternative behaviours to 50% during stall conditions comes closest to achieving the properties of the idiotypic system, but remains unable to match it in terms of all round performance.

Construcción de un prototipo de robot sembrador de maíz Agrobot II

64 p.