41 research outputs found

    A multi-hierarchical symbolic model of the environment for improving mobile robot operation

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    El trabajo desarrollado en esta tesis se centra en el estudio y aplicaci贸n de estructuras multijer谩rquicas, que representan el entorno de un robot m贸vil, con el objetivo de mejorar su capacidad de realizar tareas complejas en escenarios humanos. Un robot m贸vil debe poseer una representaci贸n simb贸lica de su entorno para poder llevar a cabo operaciones deliberativas, por ejemplo planificar tareas. Sin embargo a la hora de representar simb贸licamente entornos reales, dado su complejidad, es imprescindible contar con mecanismos capaces de organizar y facilitar el acceso a la ingente cantidad de informaci贸n que de ellos se deriva. Aparte del inconveniente de tratar con grandes cantidades de informaci贸n, existen otros problemas subyacentes de la representaci贸n simb贸lica de entornos reales, los cuales a煤n no han sido resueltos por completo en la literatura cient铆fica. Uno de ellos consiste en el mantenimiento de la representaci贸n simb贸lica optimizada con respecto a las tareas que el robot debe realizar, y coherente con el entorno en el que se desenvuelve. Otro problema, relacionado con el anterior es la creaci贸n/modificaci贸n de la informaci贸n simb贸lica a partir de informaci贸n meramente sensorial (este problema es conocido como symbol-grounding). Esta tesis estudia estos problemas y aporta soluciones mediante estructuras multijer谩rquicas. Estas estructuras simb贸licas, basadas en el concepto de abstracci贸n, imitan la forma en la que los humanos organizamos la informaci贸n espacial y permite a un robot m贸vil mejorar sus habilidades en entornos complejos. Las principales contribuciones de este trabajo son: - Se ha formalizado matem谩ticamente un modelo simb贸lico basado en m煤ltiples abstracciones (multijerarqu铆as) mediante Teor铆a de Categor铆as. Se ha desarrollado un planificador de tareas eficiente que es capaz de aprovechar la organizaci贸n jer谩rquica del modelo simb贸lico del entorno. Nuestro m茅todo ha sido validado matem谩ticamente y se han implementado y comparado dos variantes del mismo (HPWA-1 y HPWA-2). - Una instancia particular del modelo multijer谩rquico ha sido estudiada e implementada para organizar informaci贸n simb贸lica con el objetivo de mejorar simult谩neamente diferentes tareas a realizar por un robot m贸vil. - Se ha desarrollado un procedimiento que (1) construye un modelo jer谩rquico del entorno de un robot, (2) lo mantiene coherente y actualizado y (3) lo optimiza con el fin de mejorar las tareas realizadas por un robot m贸vil. - Finalmente, se ha implementado una arquitectura rob贸tica que engloba todas las cuestiones anteriormente citadas. Se han realizado pruebas reales con una silla de ruedas robotizada que ponen de manifiesto la utilidad del uso de estructuras multijer谩rquicas en rob贸tica m贸vil

    An assisted navigation method for telepresence robots

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    Telepresence robots have emerged as a new means of interaction in remote environments. However, the use of such robots is still limited due to safety and usability issues when operating in human-like environments. This work addresses these issues by enhancing the robot navigation through a collaborative control method that assists the user to negotiate obstacles. The method has been implemented in a commercial telepresence robot and a user study has been conducted in order to test the suitability of our approach.Universidad de M谩laga. Campus de Excelencia Internacional Andaluc铆a Tech

    Enhancing smart environments with mobile robots

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    Sensor networks are becoming popular nowadays in the development of smart environments. Heavily relying on static sensor and actuators, though, such environments usually lacks of versatility regarding the provided services and interaction capabilities. Here we present a framework for smart environments where a service robot is included within the sensor network acting as a mobile sensor and/or actuator. Our framework integrates on-the-shelf technologies to ensure its adaptability to a variety of sensor technologies and robotic software. Two pilot cases are presented as evaluation of our proposal.Universidad de M谩laga. Campus de Excelencia Internacional Andaluc铆a Tech

    OLT: A Toolkit for Object Labeling Applied to Robotic RGB-D Datasets

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    In this work we present the Object Labeling Toolkit (OLT), a set of software components publicly available for helping in the management and labeling of sequential RGB-D observations collected by a mobile robot. Such a robot can be equipped with an arbitrary number of RGB-D devices, possibly integrating other sensors (e.g. odometry, 2D laser scanners, etc.). OLT first merges the robot observations to generate a 3D reconstruction of the scene from which object segmentation and labeling is conveniently accomplished. The annotated labels are automatically propagated by the toolkit to each RGB-D observation in the collected sequence, providing a dense labeling of both intensity and depth images. The resulting objects鈥 labels can be exploited for many robotic oriented applications, including high-level decision making, semantic mapping, or contextual object recognition. Software components within OLT are highly customizable and expandable, facilitating the integration of already-developed algorithms. To illustrate the toolkit suitability, we describe its application to robotic RGB-D sequences taken in a home environment.Universidad de M谩laga. Campus de Excelencia Internacional Andaluc铆a Tech. Spanish grant pro- gram FPU-MICINN 2010 and the Spanish projects TAROTH: New developments toward a Robot at Home (DPI2011-25483) and PROMOVE: Advances in mobile robotics for promoting independent life of elders (DPI2014-55826-R

    UPGMpp: a Software Library for Contextual Object Recognition

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    Object recognition is a cornerstone task towards the scene understanding problem. Recent works in the field boost their perfor- mance by incorporating contextual information to the traditional use of the objects鈥 geometry and/or appearance. These contextual cues are usually modeled through Conditional Random Fields (CRFs), a partic- ular type of undirected Probabilistic Graphical Model (PGM), and are exploited by means of probabilistic inference methods. In this work we present the Undirected Probabilistic Graphical Models in C++ library (UPGMpp), an open source solution for representing, training, and per- forming inference over undirected PGMs in general, and CRFs in par- ticular. The UPGMpp library supposes a reliable and comprehensive workbench for recognition systems exploiting contextual information, in- cluding a variety of inference methods based on local search, graph cuts, and message passing approaches. This paper illustrates the virtues of the library, i.e. it is efficient, comprehensive, versatile, and easy to use, by presenting a use-case applied to the object recognition problem in home scenes from the challenging NYU2 dataset.Universidad de M谩laga. Campus de Excelencia Internacional Andaluc铆a Tech. Spanish grant program FPU-MICINN 2010 and the Spanish projects 鈥淭AROTH: New developments toward a robot at home鈥 (Ref. DPI2011-25483) and 鈥淧ROMOVE: Advances in mobile robotics for promoting independent life of elders鈥 (Ref. DPI2014-55826-R

    Experiences on a motivational learning approach for robotics in undergraduate courses

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    This paper presents an educational experience carried out in robotics undergraduate courses from two different degrees: Computer Science and Industrial Engineering, having students with diverse capabilities and motivations. The experience compares two learning strategies for the practical lessons of such courses: one relies on code snippets in Matlab to cope with typical robotic problems like robot motion, localization, and mapping, while the second strategy opts for using the ROS framework for the development of algorithms facing a competitive challenge, e.g. exploration algorithms. The obtained students鈥 opinions were instructive, reporting, for example, that although they consider harder to master ROS when compared to Matlab, it might be more useful in their (robotic related) professional careers, which enhanced their disposition to study it. They also considered that the challenge-exercises, in addition to motivate them, helped to develop their skills as engineers to a greater extent than the skeleton-code based ones. These and other conclusions will be useful in posterior courses to boost the interest and motivation of the students.Universidad de M谩laga. Campus de Excelencia Internacional Andaluc铆a Tech

    Online Context-based Object Recognition for Mobile Robots

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    This work proposes a robotic object recognition system that takes advantage of the contextual information latent in human-like environments in an online fashion. To fully leverage context, it is needed perceptual information from (at least) a portion of the scene containing the objects of interest, which could not be entirely covered by just an one-shot sensor observation. Information from a larger portion of the scenario could still be considered by progressively registering observations, but this approach experiences difficulties under some circumstances, e.g. limited and heavily demanded computational resources, dynamic environments, etc. Instead of this, the proposed recognition system relies on an anchoring process for the fast registration and propagation of objects鈥 features and locations beyond the current sensor frustum. In this way, the system builds a graphbased world model containing the objects in the scenario (both in the current and previously perceived shots), which is exploited by a Probabilistic Graphical Model (PGM) in order to leverage contextual information during recognition. We also propose a novel way to include the outcome of local object recognition methods in the PGM, which results in a decrease in the usually high CRF learning complexity. A demonstration of our proposal has been conducted employing a dataset captured by a mobile robot from restaurant-like settings, showing promising results.Universidad de M谩laga. Campus de Excelencia Internacional Andaluc铆a Tech

    Improvement of the sensory and autonomous capability of robots through olfaction: the IRO Project

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    Proyecto de Excelencia Junta de Andaluc铆a TEP2012-530Olfaction is a valuable source of information about the environment that has not been su ciently exploited in mobile robotics yet. Certainly, odor information can contribute to other sensing modalities, e.g. vision, to successfully accomplish high-level robot activities, such as task planning or execution in human environments. This paper describes the developments carried out in the scope of the IRO project, which aims at making progress in this direction by investigating mechanisms that exploit odor information (usually coming in the form of the type of volatile and its concentration) in problems like object recognition and scene-activity understanding. A distinctive aspect of this research is the special attention paid to the role of semantics within the robot perception and decisionmaking processes. The results of the IRO project have improved the robot capabilities in terms of efciency, autonomy and usefulness.Universidad de M谩laga. Campus de Excelencia Internacional Andaluc铆a Tec

    Evaluation of Using Semi-Autonomy Features in Mobile Robotic Telepresence Systems

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    Mobile robotic telepresence systems used for social interaction scenarios require that users steer robots in a remote environment. As a consequence, a heavy workload can be put on users if they are unfamiliar with using robotic telepresence units. One way to lessen this workload is to automate certain operations performed during a telepresence session in order to assist remote drivers in navigating the robot in new environments. Such operations include autonomous robot localization and navigation to certain points in the home and automatic docking of the robot to the charging station. In this paper we describe the implementation of such autonomous features along with user evaluation study. The evaluation scenario is focused on the first experience on using the system by novice users. Importantly, that the scenario taken in this study assumed that participants have as little as possible prior information about the system. Four different use-cases were identified from the user behaviour analysis.Universidad de M谩laga. Campus de Excelencia Internacional Andaluc铆a Tech. Plan Nacional de Investigaci贸n, proyecto DPI2011-25483
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