Mobile Robot Self Localization based on Multi-Antenna-RFID Reader and IC Tag Textile

This paper presents a self-localization system using multiple RFID reader antennas and High-Frequency RFID-tag textile floor for an indoor autonomous mobile robot. Conventional self-localization systems often use vision sensors and/or laser range finders and an environment model. It is difficult to estimate the exact global location if the environment has number of places that have similar shape boundaries or small number of landmarks to localize. It tends to take a long time to recover the self-localization estimation if it goes wrong at once. Vision sensors work hard in dark lighting condition. Laser range finder often fails to detect distance to a transparent wall. In addition, the self-localization becomes unstable if obstacles occlude landmarks that are important to estimate position of the robot. Door opening and closing condition affects the self- localization performance. Self-localization system based on reading RFID-tags on floor is robust against lighting condition, obstacles, furniture and doors conditions in the environment. Even if the arrangement of the obstacles or furniture in the environment is changed, it is not necessary to update the map for the self-localization. It can localize itself immediately and is free from well-known kidnapped robot problem because the RFID-tags give global po- sition information. Conventional self-localization systems based on reading RFID-tags on floor often use only one RFID reader antenna and have difficulty of orientation estimation. We have developed a self-localization system using multiple RFID reader antennas and High-Frequency RFID-tag textile floor for an indoor autonomous mobile robot. Experimental results show the validity of the proposed methods.2013 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO) Shibaura Institute of Technology, Tokyo, JAPAN November 7-9, 201

Diseño de una arquitectura robótica para mapear un lenguaje de acción a comandos de movimiento de bajo nivel para manipulación hábil

This paper gives an overview of a robotic architecture meant for skillful manipulation. This design is meant to close the gap between the high level layer (reasoning and planing layer) and the object model system (physical control layer). This architecture proposes an interface layer that allows, in a meaningful way, to connect atomic tasks with controller inputs. In this paper, we discuss how specific complex tasks can be resolved by this system; we analyze the affordance unit design and, we overview the future challenges in the implemenation of the whole system.Este artículo ofrece una visión general de una arquitectura robótica destinada a la manipulación hábil. Este diseño está destinado a cerrar la brecha entre la capa de alto nivel (capa de razonamiento y planificación) y el sistema de modelo de objetos (capa de control físico). Esta arquitectura propone una capa de interfaz que permite, de manera significativa, conectar tareas básicas con el controlador. En este artículo, discutimos cómo este sistema puede resolver tareas complejas específicas; analizamos el diseño de la unidad de accesibilidad y presentamos una visión general de los desafíos futuros en la implementación de todo el sistema.Universidad de Costa Rica/[322-B6-279]/UCR/Costa RicaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ingeniería::Instituto Investigaciones en Ingeniería (INII)UCR::Vicerrectoría de Docencia::Ingeniería::Facultad de Ingeniería::Escuela de Ingeniería EléctricaUCR::Vicerrectoría de Investigación::Sistema de Estudios de Posgrado::Ingeniería::Maestría Académica en Ingeniería Eléctric

Bayesian & AI driven Embedded Perception and Decision-making. Application to Autonomous Navigation in Complex, Dynamic, Uncertain and Human-populated Environments.Synoptic of Research Activity, Period 2004-20 and beyond

Robust perception & Decision-making for safe navigation in open and dynamic environments populated by human beings is an open and challenging scientific problem. Traditional approaches do not provide adequate solutions for these problems, mainly because these environments are partially unknown, open and subject to strong constraints to be satisfied (in particular high dynamicity and uncertainty). This means that the proposed solutions have to take simultaneously into account characteristics such as real-time processing, temporary occultation or false detections, dynamic changes in the scene, prediction of the future dynamic behaviors of the surrounding moving entities, continuous assessment of the collision risk, or decision-making for safe navigation. This research report presents how we have addressed this problem over the two last decades, as well as an outline of our Bayesian & IA approach for solving the Embedded Perception and Decision-making problems

Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

Automatic Initialization System for Home-based Robotics Service Environment

芝浦工業大学201

From Babies to Robots: The Contribution of Developmental Robotics to Developmental Psychology

© 2018 The Society for Research in Child Development, Inc. The latest developments in artificial intelligence (AI) and machine learning, and the parallel advances in robotics, have contributed recently to a shift in the scientific approach to modeling human intelligence. These innovations, accompanied by the new emphasis on embodied and grounded cognition in AI and psychology, have led to the establishment of the field of developmental robotics. This field features an interdisciplinary approach, built on collaboration between cognitive robotics and child psychology, to the autonomous design of behavioral and cognitive capabilities in artificial cognitive agents, such as robots, which is inspired by developmental principles and mechanisms observed in children. In this article, we illustrate the benefits of this approach by presenting a case study of a baby robot with a focus on the role of embodiment during early word learning, as well as an overview of several developmental robotics model of perceptual, social, and language development

Robot Learning from Demonstration in Robotic Assembly: A Survey

Learning from demonstration (LfD) has been used to help robots to implement manipulation tasks autonomously, in particular, to learn manipulation behaviors from observing the motion executed by human demonstrators. This paper reviews recent research and development in the field of LfD. The main focus is placed on how to demonstrate the example behaviors to the robot in assembly operations, and how to extract the manipulation features for robot learning and generating imitative behaviors. Diverse metrics are analyzed to evaluate the performance of robot imitation learning. Specifically, the application of LfD in robotic assembly is a focal point in this paper

Dual Quaternions as Constraints in 4D-DPM Models for Pose Estimation

This work was partially financed by Plan Nacional de Investigacion y Desarrollo (I+D), Comision Interministerial de Ciencia y Tecnologia (FEDER-CICYT) under the project DPI2013-44227-R.Martínez Bertí, E.; Sánchez Salmerón, AJ.; Ricolfe Viala, C. (2017). Dual Quaternions as Constraints in 4D-DPM Models for Pose Estimation. Sensors. 17 (8)(1913):1-16. https://doi.org/10.3390/s17081913S11617 (8)191

R2T2 : Robotics to Integrate Educational Efforts in South Africa and Europe

This paper presents the first cross-continental collaborative robotic event based around education. It was entitled R2T2 and it involved more than 100 children from Europe and Africa. Based on remote programming, video streaming feedback, and a scenario of collaborative space rescue, R2T2 focused on pedagogical elements that are fundamentally different than those characterizing classic robotic competitions. The value of these educational actions is shown through the results of a survey conducted among the participants; the working methodologies by the African students were significantly enhanced and there was a broad inclusion in general, despite the fact that some gender issues lingered. This paper's contribution is to demonstrate an approach to implementing a north-south collaboration to get school students excited about robotics and the problem-solving skills required in engineering