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

Tracking and modeling focus of attention in meetings [online]

Abstract This thesis addresses the problem of tracking the focus of attention of people. In particular, a system to track the focus of attention of participants in meetings is developed. Obtaining knowledge about a person\u27s focus of attention is an important step towards a better understanding of what people do, how and with what or whom they interact or to what they refer. In meetings, focus of attention can be used to disambiguate the addressees of speech acts, to analyze interaction and for indexing of meeting transcripts. Tracking a user\u27s focus of attention also greatly contributes to the improvement of human­computer interfaces since it can be used to build interfaces and environments that become aware of what the user is paying attention to or with what or whom he is interacting. The direction in which people look; i.e., their gaze, is closely related to their focus of attention. In this thesis, we estimate a subject\u27s focus of attention based on his or her head orientation. While the direction in which someone looks is determined by head orientation and eye gaze, relevant literature suggests that head orientation alone is a su#cient cue for the detection of someone\u27s direction of attention during social interaction. We present experimental results from a user study and from several recorded meetings that support this hypothesis. We have developed a Bayesian approach to model at whom or what someone is look­ ing based on his or her head orientation. To estimate head orientations in meetings, the participants\u27 faces are automatically tracked in the view of a panoramic camera and neural networks are used to estimate their head orientations from pre­processed images of their faces. Using this approach, the focus of attention target of subjects could be correctly identified during 73% of the time in a number of evaluation meet­ ings with four participants. In addition, we have investigated whether a person\u27s focus of attention can be pre­dicted from other cues. Our results show that focus of attention is correlated to who is speaking in a meeting and that it is possible to predict a person\u27s focus of attention based on the information of who is talking or was talking before a given moment. We have trained neural networks to predict at whom a person is looking, based on information about who was speaking. Using this approach we were able to predict who is looking at whom with 63% accuracy on the evaluation meetings using only information about who was speaking. We show that by using both head orientation and speaker information to estimate a person\u27s focus, the accuracy of focus detection can be improved compared to just using one of the modalities for focus estimation. To demonstrate the generality of our approach, we have built a prototype system to demonstrate focus­aware interaction with a household robot and other smart appliances in a room using the developed components for focus of attention tracking. In the demonstration environment, a subject could interact with a simulated household robot, a speech­enabled VCR or with other people in the room, and the recipient of the subject\u27s speech was disambiguated based on the user\u27s direction of attention. Zusammenfassung Die vorliegende Arbeit beschäftigt sich mit der automatischen Bestimmung und Ver­folgung des Aufmerksamkeitsfokus von Personen in Besprechungen. Die Bestimmung des Aufmerksamkeitsfokus von Personen ist zum Verständnis und zur automatischen Auswertung von Besprechungsprotokollen sehr wichtig. So kann damit beispielsweise herausgefunden werden, wer zu einem bestimmten Zeitpunkt wen angesprochen hat beziehungsweise wer wem zugehört hat. Die automatische Bestim­mung des Aufmerksamkeitsfokus kann desweiteren zur Verbesserung von Mensch-Maschine­Schnittstellen benutzt werden. Ein wichtiger Hinweis auf die Richtung, in welche eine Person ihre Aufmerksamkeit richtet, ist die Kopfstellung der Person. Daher wurde ein Verfahren zur Bestimmung der Kopfstellungen von Personen entwickelt. Hierzu wurden künstliche neuronale Netze benutzt, welche als Eingaben vorverarbeitete Bilder des Kopfes einer Person erhalten, und als Ausgabe eine Schätzung der Kopfstellung berechnen. Mit den trainierten Netzen wurde auf Bilddaten neuer Personen, also Personen, deren Bilder nicht in der Trainingsmenge enthalten waren, ein mittlerer Fehler von neun bis zehn Grad für die Bestimmung der horizontalen und vertikalen Kopfstellung erreicht. Desweiteren wird ein probabilistischer Ansatz zur Bestimmung von Aufmerksamkeits­zielen vorgestellt. Es wird hierbei ein Bayes\u27scher Ansatzes verwendet um die A­posterior iWahrscheinlichkeiten verschiedener Aufmerksamkteitsziele, gegeben beobachteter Kopfstellungen einer Person, zu bestimmen. Die entwickelten Ansätze wurden auf mehren Besprechungen mit vier bis fünf Teilnehmern evaluiert. Ein weiterer Beitrag dieser Arbeit ist die Untersuchung, inwieweit sich die Blickrich­tung der Besprechungsteilnehmer basierend darauf, wer gerade spricht, vorhersagen läßt. Es wurde ein Verfahren entwickelt um mit Hilfe von neuronalen Netzen den Fokus einer Person basierend auf einer kurzen Historie der Sprecherkonstellationen zu schätzen. Wir zeigen, dass durch Kombination der bildbasierten und der sprecherbasierten Schätzung des Aufmerksamkeitsfokus eine deutliche verbesserte Schätzung erreicht werden kann. Insgesamt wurde mit dieser Arbeit erstmals ein System vorgestellt um automatisch die Aufmerksamkeit von Personen in einem Besprechungsraum zu verfolgen. Die entwickelten Ansätze und Methoden können auch zur Bestimmung der Aufmerk­samkeit von Personen in anderen Bereichen, insbesondere zur Steuerung von comput­erisierten, interaktiven Umgebungen, verwendet werden. Dies wird an einer Beispielapplikation gezeigt

Contemporary Robotics

This book book is a collection of 18 chapters written by internationally recognized experts and well-known professionals of the field. Chapters contribute to diverse facets of contemporary robotics and autonomous systems. The volume is organized in four thematic parts according to the main subjects, regarding the recent advances in the contemporary robotics. The first thematic topics of the book are devoted to the theoretical issues. This includes development of algorithms for automatic trajectory generation using redudancy resolution scheme, intelligent algorithms for robotic grasping, modelling approach for reactive mode handling of flexible manufacturing and design of an advanced controller for robot manipulators. The second part of the book deals with different aspects of robot calibration and sensing. This includes a geometric and treshold calibration of a multiple robotic line-vision system, robot-based inline 2D/3D quality monitoring using picture-giving and laser triangulation, and a study on prospective polymer composite materials for flexible tactile sensors. The third part addresses issues of mobile robots and multi-agent systems, including SLAM of mobile robots based on fusion of odometry and visual data, configuration of a localization system by a team of mobile robots, development of generic real-time motion controller for differential mobile robots, control of fuel cells of mobile robots, modelling of omni-directional wheeled-based robots, building of hunter- hybrid tracking environment, as well as design of a cooperative control in distributed population-based multi-agent approach. The fourth part presents recent approaches and results in humanoid and bioinspirative robotics. It deals with design of adaptive control of anthropomorphic biped gait, building of dynamic-based simulation for humanoid robot walking, building controller for perceptual motor control dynamics of humans and biomimetic approach to control mechatronic structure using smart materials

Déploiement optimal de réseaux de capteurs dans des environnements intérieurs en support à la navigation des personnes à mobilité réduite

La participation sociale des personnes ayant une incapacité (PAI) est l'un des enjeux majeurs de notre société. La participation sociale des PAI est influencée par les résultats des interactions entre les facteurs personnels et les facteurs environnementaux (physiques et sociaux). L'une des activités quotidiennes les plus importantes en milieu urbain est la mobilité, ce qui est fondamental pour la participation sociale des PAI. L'environnement urbain est composé des infrastructures et des services principalement conçus pour les personnes sans incapacités et ne prend pas en compte les besoins spécifiques des PAI. Dans ce contexte, la conception et le développement des environnements intelligents peuvent contribuer à une meilleure mobilité et participation sociale des PAI grâce à l'avancement récent de technologie de l'information et de télécommunication ainsi que de réseaux de capteurs. Cependant, le déploiement de réseaux de capteurs en tant que technologie d'assistance pour améliorer la mobilité des personnes n'est conçu que sur la base des modèles trop simplistes de l'environnement physique. Bien que des approches de déploiement de réseaux de capteurs aient été développées ces dernières années, la plupart d'entre elles ont considéré le modèle simple des capteurs (cercle ou sphérique dans le meilleur des cas) et l'environnement 2D, (sans obstacle), indépendamment des besoins des PAI lors de leur mobilité. À cet égard, l'objectif global de cette thèse est le déploiement optimal de réseau de capteurs dans un environnement intérieur pour améliorer l'efficacité de la mobilité des personnes à mobilité réduite (PMR). Plus spécifiquement, nous sommes intéressés à la mobilité des personnes utilisatrices de fauteuil roulant manuel. Pour atteindre cet objectif global, trois objectifs spécifiques sont identifiés. Premièrement, nous proposons un cadre conceptuel pour l'évaluation de la lisibilité de l'environnement intérieur pour les PMR, afin de déterminer la méthode appropriée pour évaluer les interactions entre les facteurs personnels et les facteurs environnementaux (par exemple, pentes, rampes, marches, etc.). Deuxièmement, nous développons un algorithme d'optimisation locale basé sur la structure Voronoi 3D pour le déploiement de capteurs dans l'environnement intérieur 3D pour s'attaquer à la complexité de la structure de l'environnement intérieur (par exemple, différentes hauteurs de plafonds) afin de maximiser la couverture du réseau. Troisièmement, pour aider la mobilité des PMR, nous développons un algorithme d'optimisation ciblé pour le déploiement de capteurs multi-types dans l'environnement intérieur en tenant compte du cadre d'évaluation de la lisibilité pour les PMR. La question la plus importante de cette recherche est la suivante : quels sont les emplacements optimaux pour un ensemble des capteurs pour le positionnement et le guidage des PMR dans l'environnement intérieur complexe 3D. Pour répondre à cette question, les informations sur les caractéristiques des capteurs, les éléments environnementaux et la lisibilité des PMR ont été intégrés dans les algorithmes d'optimisation locale pour le déploiement de réseaux de capteurs multi-types, afin d'améliorer la couverture du réseau et d'aider efficacement les PMR lors de leur mobilité. Dans ce processus, le diagramme de Voronoi 3D, en tant que structure géométrique, est utilisé pour optimiser l'emplacement des capteurs en fonction des caractéristiques des capteurs, des éléments environnementaux et de la lisibilité des PMR. L'optimisation locale proposée a été mise en œuvre et testée avec plusieurs scénarios au Centre des congrès de Québec. La comparaison des résultats obtenus avec ceux des autres algorithmes démontre une plus grande efficacité de l'approche proposée dans cette recherche.Social participation of people with disabilities (PWD) is one of the challenging problems in our society. Social participation of PWD is influenced by results from the interactions between personal characteristics and the physical and social environments. One of the most significant daily activities in the urban environment is mobility which impacts on the social participation of PWD. The urban environment includes infrastructure and services are mostly designed for people without any disability and does not consider the specific needs of PWD. In this context, the design and development of intelligent environments can contribute to better mobility and social participation of PWD by leveraging the recent advancement in information and telecommunications technologies as well as sensor networks. Sensor networks, as an assistive technology for improving the mobility of people are generally designed based on the simplistic models of physical environment. Although sensor networks deployment approaches have been developed in recent years, the majority of them have considered the simple model of sensors (circle or spherical in the best case) and the environment (2D, without obstacles) regardless of the PWD needs during their mobility. In this regard, the global objective of this thesis is the determination of the position and type of sensors to enhance the efficiency of the people with motor disabilities (PWMD) mobility. We are more specifically interested in the mobility of people using manual wheelchair. To achieve this global objective, three specific objectives are demarcated. First, a framework is developed for legibility assessment of the indoor environment for PWMD to determine the appropriate method to evaluate the interactions between personal factors with environmental factors (e.g. slops, ramps, steps, etc.). Then, a local optimization algorithm based on 3D Voronoi structure for sensor deployment in the 3D indoor environment is developed to tackle the complexity of structure of indoor environment (e.g., various ceilings' height) to maximize the network coverage. Next, a purpose-oriented optimization algorithm for multi-type sensor deployment in the indoor environment to help the PWMD mobility is developed with consideration of the legibility assessment framework for PWMD. In this thesis, the most important question of this research is where the optimal places of sensors are for efficient guidance of the PWMD in their mobility in 3D complex indoor environments. To answer this question, the information of sensors characteristics, environmental elements and legibility of PWMD have been integrated into the local optimization algorithms for multi-type sensor networks deployment to enhance the network coverage as well as efficiently help the PWMD during their mobility. In this process, Voronoi diagram as a geometrical structure is used to change the sensors' location based on the sensor characteristics, environmental elements and legibility of PWMD. The proposed local optimization is implemented and tested for several scenarios in Quebec City Convention Centre. The obtained results show that these integration in our approach enhance its effectiveness compared to the existing methods

Evaluation of Multi-sensory Feedback in Virtual and Real Remote Environments in a USAR Robot Teleoperation Scenario

The area of Human-Robot Interaction deals with problems not only related to robots interacting with humans, but also with problems related to humans interacting and controlling robots. This dissertation focuses on the latter and evaluates multi-sensory (vision, hearing, touch, smell) feedback interfaces as a means to improve robot-operator cognition and performance. A set of four empirical studies using both simulated and real robotic systems evaluated a set of multi-sensory feedback interfaces with various levels of complexity. The task scenario for the robot in these studies involved the search for victims in a debris-filled environment after a fictitious catastrophic event (e.g., earthquake) took place. The results show that, if well-designed, multi-sensory feedback interfaces can indeed improve the robot operator data perception and performance. Improvements in operator performance were detected for navigation and search tasks despite minor increases in workload. In fact, some of the multi-sensory interfaces evaluated even led to a reduction in workload. The results also point out that redundant feedback is not always beneficial to the operator. While introducing the concept of operator omni-directional perception, that is, the operator’s capability of perceiving data or events coming from all senses and in all directions, this work explains that feedback redundancy is only beneficial when it enhances the operator omni-directional perception of data relevant to the task at hand. Last, the comprehensive methodology employed and refined over the course of the four studies is suggested as a starting point for the design of future HRI user studies. In summary, this work sheds some light on the benefits and challenges multi-sensory feedback interfaces bring, specifically on teleoperated robotics. It adds to our current understanding of these kinds of interfaces and provides a few insights to assist the continuation of research in the area

Mobile Robots Navigation

Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described

2D-barcode for mobile devices

2D-barcodes were designed to carry significantly more data than its 1D counterpart. These codes are often used in industrial information tagging applications where high data capacity, mobility, and data robustness are required. Wireless mobile devices such as camera phones and Portable Digital Assistants (PDAs) have evolved from just a mobile voice communication device to what is now a mobile multimedia computing platform. Recent integration of these two mobile technologies has sparked some interesting applications where 2D-barcodes work as visual tags and/or information source and camera phones performs image processing tasks on the device itself. One of such applications is hyperlink establishment. The 2D symbol captured by a camera phone is decoded by the software installed in the phone. Then the web site indicated by the data encoded in a symbol is automatically accessed and shown in the display of the camera phone. Nonetheless, this new mobile applications area is still at its infancy. Each proposed mobile 2D-barcode application has its own choice of code, but no standard exists nor is there any study done on what are the criteria for setting a standard 2D-barcode for mobile phones. This study intends to address this void. The first phase of the study is qualitative examination. In order to select a best standard 2D-barcode, firstly, features desirable for a standard 2D-barcode that is optimized for the mobile phone platform are identified. The second step is to establish the criteria based on the features identified. These features are based on the operating limitations and attributes of camera phones in general use today. All published and accessible 2D-barcodes are thoroughly examined in terms of criteria set for the selection of a best 2D-barcode for camera phone applications. In the second phase, the 2D-barcodes that have higher potential to be chosen as a standard code are experimentally examined against the three criteria: light condition, distance, whether or not a 2D-barcode supports VGA resolution. Each sample 2D-barcode is captured by a camera phone with VGA resolution and the outcome is tested using an image analysis tool written in the scientific language called MATLAB. The outcome of this study is the selection of the most suitable 2D-barcode for applications where mobile devices such as camera phones are utilized

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Vision Sensors and Edge Detection

Vision Sensors and Edge Detection book reflects a selection of recent developments within the area of vision sensors and edge detection. There are two sections in this book. The first section presents vision sensors with applications to panoramic vision sensors, wireless vision sensors, and automated vision sensor inspection, and the second one shows image processing techniques, such as, image measurements, image transformations, filtering, and parallel computing

30th International Conference on Information Modelling and Knowledge Bases

Information modelling is becoming more and more important topic for researchers, designers, and users of information systems. The amount and complexity of information itself, the number of abstraction levels of information, and the size of databases and knowledge bases are continuously growing. Conceptual modelling is one of the sub-areas of information modelling. The aim of this conference is to bring together experts from different areas of computer science and other disciplines, who have a common interest in understanding and solving problems on information modelling and knowledge bases, as well as applying the results of research to practice. We also aim to recognize and study new areas on modelling and knowledge bases to which more attention should be paid. Therefore philosophy and logic, cognitive science, knowledge management, linguistics and management science are relevant areas, too. In the conference, there will be three categories of presentations, i.e. full papers, short papers and position papers