212 research outputs found

    Humanoid Robots

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    For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion

    Development of new intelligent autonomous robotic assistant for hospitals

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    Continuous technological development in modern societies has increased the quality of life and average life-span of people. This imposes an extra burden on the current healthcare infrastructure, which also creates the opportunity for developing new, autonomous, assistive robots to help alleviate this extra workload. The research question explored the extent to which a prototypical robotic platform can be created and how it may be implemented in a hospital environment with the aim to assist the hospital staff with daily tasks, such as guiding patients and visitors, following patients to ensure safety, and making deliveries to and from rooms and workstations. In terms of major contributions, this thesis outlines five domains of the development of an actual robotic assistant prototype. Firstly, a comprehensive schematic design is presented in which mechanical, electrical, motor control and kinematics solutions have been examined in detail. Next, a new method has been proposed for assessing the intrinsic properties of different flooring-types using machine learning to classify mechanical vibrations. Thirdly, the technical challenge of enabling the robot to simultaneously map and localise itself in a dynamic environment has been addressed, whereby leg detection is introduced to ensure that, whilst mapping, the robot is able to distinguish between people and the background. The fourth contribution is geometric collision prediction into stabilised dynamic navigation methods, thus optimising the navigation ability to update real-time path planning in a dynamic environment. Lastly, the problem of detecting gaze at long distances has been addressed by means of a new eye-tracking hardware solution which combines infra-red eye tracking and depth sensing. The research serves both to provide a template for the development of comprehensive mobile assistive-robot solutions, and to address some of the inherent challenges currently present in introducing autonomous assistive robots in hospital environments.Open Acces

    Robot Navigation in Human Environments

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    For the near future, we envision service robots that will help us with everyday chores in home, office, and urban environments. These robots need to work in environments that were designed for humans and they have to collaborate with humans to fulfill their tasks. In this thesis, we propose new methods for communicating, transferring knowledge, and collaborating between humans and robots in four different navigation tasks. In the first application, we investigate how automated services for giving wayfinding directions can be improved to better address the needs of the human recipients. We propose a novel method based on inverse reinforcement learning that learns from a corpus of human-written route descriptions what amount and type of information a route description should contain. By imitating the human teachers' description style, our algorithm produces new route descriptions that sound similarly natural and convey similar information content, as we show in a user study. In the second application, we investigate how robots can leverage background information provided by humans for exploring an unknown environment more efficiently. We propose an algorithm for exploiting user-provided information such as sketches or floor plans by combining a global exploration strategy based on the solution of a traveling salesman problem with a local nearest-frontier-first exploration scheme. Our experiments show that the exploration tours are significantly shorter and that our system allows the user to effectively select the areas that the robot should explore. In the second part of this thesis, we focus on humanoid robots in home and office environments. The human-like body plan allows humanoid robots to navigate in environments and operate tools that were designed for humans, making humanoid robots suitable for a wide range of applications. As localization and mapping are prerequisites for all navigation tasks, we first introduce a novel feature descriptor for RGB-D sensor data and integrate this building block into an appearance-based simultaneous localization and mapping system that we adapt and optimize for the usage on humanoid robots. Our optimized system is able to track a real Nao humanoid robot more accurately and more robustly than existing approaches. As the third application, we investigate how humanoid robots can cover known environments efficiently with their camera, for example for inspection or search tasks. We extend an existing next-best-view approach by integrating inverse reachability maps, allowing us to efficiently sample and check collision-free full-body poses. Our approach enables the robot to inspect as much of the environment as possible. In our fourth application, we extend the coverage scenario to environments that also include articulated objects that the robot has to actively manipulate to uncover obstructed regions. We introduce algorithms for navigation subtasks that run highly parallelized on graphics processing units for embedded devices. Together with a novel heuristic for estimating utility maps, our system allows to find high-utility camera poses for efficiently covering environments with articulated objects. All techniques presented in this thesis were implemented in software and thoroughly evaluated in user studies, simulations, and experiments in both artificial and real-world environments. Our approaches advance the state of the art towards universally usable robots in everyday environments.Roboternavigation in menschlichen Umgebungen In naher Zukunft erwarten wir Serviceroboter, die uns im Haushalt, im Büro und in der Stadt alltägliche Arbeiten abnehmen. Diese Roboter müssen in für Menschen gebauten Umgebungen zurechtkommen und sie müssen mit Menschen zusammenarbeiten um ihre Aufgaben zu erledigen. In dieser Arbeit schlagen wir neue Methoden für die Kommunikation, Wissenstransfer und Zusammenarbeit zwischen Menschen und Robotern bei Navigationsaufgaben in vier Anwendungen vor. In der ersten Anwendung untersuchen wir, wie automatisierte Dienste zur Generierung von Wegbeschreibungen verbessert werden können, um die Beschreibungen besser an die Bedürfnisse der Empfänger anzupassen. Wir schlagen eine neue Methode vor, die inverses bestärkendes Lernen nutzt, um aus einem Korpus von von Menschen geschriebenen Wegbeschreibungen zu lernen, wie viel und welche Art von Information eine Wegbeschreibung enthalten sollte. Indem unser Algorithmus den Stil der Wegbeschreibungen der menschlichen Lehrer imitiert, kann der Algorithmus neue Wegbeschreibungen erzeugen, die sich ähnlich natürlich anhören und einen ähnlichen Informationsgehalt vermitteln, was wir in einer Benutzerstudie zeigen. In der zweiten Anwendung untersuchen wir, wie Roboter von Menschen bereitgestellte Hintergrundinformationen nutzen können, um eine bisher unbekannte Umgebung schneller zu erkunden. Wir schlagen einen Algorithmus vor, der Hintergrundinformationen wie Gebäudegrundrisse oder Skizzen nutzt, indem er eine globale Explorationsstrategie basierend auf der Lösung eines Problems des Handlungsreisenden kombiniert mit einer lokalen Explorationsstrategie. Unsere Experimente zeigen, dass die Erkundungstouren signifikant kürzer werden und dass der Benutzer mit unserem System effektiv die zu erkundenden Regionen spezifizieren kann. Der zweite Teil dieser Arbeit konzentriert sich auf humanoide Roboter in Umgebungen zu Hause und im Büro. Der menschenähnliche Körperbau ermöglicht es humanoiden Robotern, in Umgebungen zu navigieren und Werkzeuge zu benutzen, die für Menschen gebaut wurden, wodurch humanoide Roboter für vielfältige Aufgaben einsetzbar sind. Da Lokalisierung und Kartierung Grundvoraussetzungen für alle Navigationsaufgaben sind, führen wir zunächst einen neuen Merkmalsdeskriptor für RGB-D-Sensordaten ein und integrieren diesen Baustein in ein erscheinungsbasiertes simultanes Lokalisierungs- und Kartierungsverfahren, das wir an die Besonderheiten von humanoiden Robotern anpassen und optimieren. Unser System kann die Position eines realen humanoiden Roboters genauer und robuster verfolgen, als es mit existierenden Ansätzen möglich ist. Als dritte Anwendung untersuchen wir, wie humanoide Roboter bekannte Umgebungen effizient mit ihrer Kamera abdecken können, beispielsweise zu Inspektionszwecken oder zum Suchen eines Gegenstands. Wir erweitern ein bestehendes Verfahren, das die nächstbeste Beobachtungsposition berechnet, durch inverse Erreichbarkeitskarten, wodurch wir kollisionsfreie Ganzkörperposen effizient generieren und prüfen können. Unser Ansatz ermöglicht es dem Roboter, so viel wie möglich von der Umgebung zu untersuchen. In unserer vierten Anwendung erweitern wir dieses Szenario um Umgebungen, die auch bewegbare Gegenstände enthalten, die der Roboter aktiv bewegen muss um verdeckte Regionen zu sehen. Wir führen Algorithmen für Teilprobleme ein, die hoch parallelisiert auf Grafikkarten von eingebetteten Systemen ausgeführt werden. Zusammen mit einer neuen Heuristik zur Schätzung von Nutzenkarten ermöglicht dies unserem System Beobachtungspunkte mit hohem Nutzen zu finden, um Umgebungen mit bewegbaren Objekten effizient zu inspizieren. Alle vorgestellten Techniken wurden in Software implementiert und sorgfältig evaluiert in Benutzerstudien, Simulationen und Experimenten in künstlichen und realen Umgebungen. Unsere Verfahren bringen den Stand der Forschung voran in Richtung universell einsetzbarer Roboter in alltäglichen Umgebungen

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

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    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

    Peripersonal Space in the Humanoid Robot iCub

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    Developing behaviours for interaction with objects close to the body is a primary goal for any organism to survive in the world. Being able to develop such behaviours will be an essential feature in autonomous humanoid robots in order to improve their integration into human environments. Adaptable spatial abilities will make robots safer and improve their social skills, human-robot and robot-robot collaboration abilities. This work investigated how a humanoid robot can explore and create action-based representations of its peripersonal space, the region immediately surrounding the body where reaching is possible without location displacement. It presents three empirical studies based on peripersonal space findings from psychology, neuroscience and robotics. The experiments used a visual perception system based on active-vision and biologically inspired neural networks. The first study investigated the contribution of binocular vision in a reaching task. Results indicated the signal from vergence is a useful embodied depth estimation cue in the peripersonal space in humanoid robots. The second study explored the influence of morphology and postural experience on confidence levels in reaching assessment. Results showed that a decrease of confidence when assessing targets located farther from the body, possibly in accordance to errors in depth estimation from vergence for longer distances. Additionally, it was found that a proprioceptive arm-length signal extends the robot’s peripersonal space. The last experiment modelled development of the reaching skill by implementing motor synergies that progressively unlock degrees of freedom in the arm. The model was advantageous when compared to one that included no developmental stages. The contribution to knowledge of this work is extending the research on biologically-inspired methods for building robots, presenting new ways to further investigate the robotic properties involved in the dynamical adaptation to body and sensing characteristics, vision-based action, morphology and confidence levels in reaching assessment.CONACyT, Mexico (National Council of Science and Technology

    Reasoning about space for human-robot interaction

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    L'interaction Homme-Robot est un domaine de recherche qui se développe de manière exponentielle durant ces dernières années, ceci nous procure de nouveaux défis au raisonnement géométrique du robot et au partage d'espace. Le robot pour accomplir une tâche, doit non seulement raisonner sur ses propres capacités, mais également prendre en considération la perception humaine, c'est à dire "Le robot doit se placer du point de vue de l'humain". Chez l'homme, la capacité de prise de perspective visuelle commence à se manifester à partir du 24ème mois. Cette capacité est utilisée pour déterminer si une autre personne peut voir un objet ou pas. La mise en place de ce genre de capacités sociales améliorera les capacités cognitives du robot et aidera le robot pour une meilleure interaction avec les hommes. Dans ce travail, nous présentons un mécanisme de raisonnement spatial de point de vue géométrique qui utilise des concepts psychologiques de la "prise de perspective" et "de la rotation mentale" dans deux cadres généraux: - La planification de mouvement pour l'interaction homme-robot: le robot utilise "la prise de perspective égocentrique" pour évaluer plusieurs configurations où le robot peut effectuer différentes tâches d'interaction. - Une interaction face à face entre l'homme et le robot : le robot emploie la prise de point de vue de l'humain comme un outil géométrique pour comprendre l'attention et l'intention humaine afin d'effectuer des tâches coopératives.Human Robot Interaction is a research area that is growing exponentially in last years. This fact brings new challenges to the robot's geometric reasoning and space sharing abilities. The robot should not only reason on its own capacities but also consider the actual situation by looking from human's eyes, thus "putting itself into human's perspective". In humans, the "visual perspective taking" ability begins to appear by 24 months of age and is used to determine if another person can see an object or not. The implementation of this kind of social abilities will improve the robot's cognitive capabilities and will help the robot to perform a better interaction with human beings. In this work, we present a geometric spatial reasoning mechanism that employs psychological concepts of "perspective taking" and "mental rotation" in two general frameworks: - Motion planning for human-robot interaction: where the robot uses "egocentric perspective taking" to evaluate several configurations where the robot is able to perform different tasks of interaction. - A face-to-face human-robot interaction: where the robot uses perspective taking of the human as a geometric tool to understand the human attention and intention in order to perform cooperative tasks

    Model-Based Environmental Visual Perception for Humanoid Robots

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    The visual perception of a robot should answer two fundamental questions: What? and Where? In order to properly and efficiently reply to these questions, it is essential to establish a bidirectional coupling between the external stimuli and the internal representations. This coupling links the physical world with the inner abstraction models by sensor transformation, recognition, matching and optimization algorithms. The objective of this PhD is to establish this sensor-model coupling

    The Future of Humanoid Robots

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    This book provides state of the art scientific and engineering research findings and developments in the field of humanoid robotics and its applications. It is expected that humanoids will change the way we interact with machines, and will have the ability to blend perfectly into an environment already designed for humans. The book contains chapters that aim to discover the future abilities of humanoid robots by presenting a variety of integrated research in various scientific and engineering fields, such as locomotion, perception, adaptive behavior, human-robot interaction, neuroscience and machine learning. The book is designed to be accessible and practical, with an emphasis on useful information to those working in the fields of robotics, cognitive science, artificial intelligence, computational methods and other fields of science directly or indirectly related to the development and usage of future humanoid robots. The editor of the book has extensive R&D experience, patents, and publications in the area of humanoid robotics, and his experience is reflected in editing the content of the book

    Climbing and Walking Robots

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    Nowadays robotics is one of the most dynamic fields of scientific researches. The shift of robotics researches from manufacturing to services applications is clear. During the last decades interest in studying climbing and walking robots has been increased. This increasing interest has been in many areas that most important ones of them are: mechanics, electronics, medical engineering, cybernetics, controls, and computers. Today’s climbing and walking robots are a combination of manipulative, perceptive, communicative, and cognitive abilities and they are capable of performing many tasks in industrial and non- industrial environments. Surveillance, planetary exploration, emergence rescue operations, reconnaissance, petrochemical applications, construction, entertainment, personal services, intervention in severe environments, transportation, medical and etc are some applications from a very diverse application fields of climbing and walking robots. By great progress in this area of robotics it is anticipated that next generation climbing and walking robots will enhance lives and will change the way the human works, thinks and makes decisions. This book presents the state of the art achievments, recent developments, applications and future challenges of climbing and walking robots. These are presented in 24 chapters by authors throughtot the world The book serves as a reference especially for the researchers who are interested in mobile robots. It also is useful for industrial engineers and graduate students in advanced study
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