1,655 research outputs found

    On the Integration of Adaptive and Interactive Robotic Smart Spaces

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    © 2015 Mauro Dragone et al.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. (CC BY-NC-ND 3.0)Enabling robots to seamlessly operate as part of smart spaces is an important and extended challenge for robotics R&D and a key enabler for a range of advanced robotic applications, such as AmbientAssisted Living (AAL) and home automation. The integration of these technologies is currently being pursued from two largely distinct view-points: On the one hand, people-centred initiatives focus on improving the user’s acceptance by tackling human-robot interaction (HRI) issues, often adopting a social robotic approach, and by giving to the designer and - in a limited degree – to the final user(s), control on personalization and product customisation features. On the other hand, technologically-driven initiatives are building impersonal but intelligent systems that are able to pro-actively and autonomously adapt their operations to fit changing requirements and evolving users’ needs,but which largely ignore and do not leverage human-robot interaction and may thus lead to poor user experience and user acceptance. In order to inform the development of a new generation of smart robotic spaces, this paper analyses and compares different research strands with a view to proposing possible integrated solutions with both advanced HRI and online adaptation capabilities.Peer reviewe

    Approaching a person in a socially acceptable manner using expanding random trees

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    In real world scenarios for mobile robots, socially acceptable navigation is a key component to interact naturally with other persons. On the one hand this enables a robot to behave more human-like, and on the other hand it increases the acceptance of the user towards the robot as an interaction partner. As part of this research field, we present in this paper a strategy of approaching a person in a socially acceptable manner. Therefore, we use the theory of ”personal space” and present a method of modeling this space to enable a mobile robot to approach a person from the front. We use a standard Dynamic Window Approach to control the robot motion and, since the personal space model could not be used directly, a graph planner in configuration space, to plan an optimal path by expanding the graph with the use of the DWA’s update rule. Additionally, we give a proof of concept with first preliminary experiments

    Impact of decision-making system in social navigation

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    [EN] Facing human activity-aware navigation with a cognitive architecture raises several difficulties integrating the components and orchestrating behaviors and skills to perform social tasks. In a real-world scenario, the navigation system should not only consider individuals like obstacles. It is necessary to offer particular and dynamic people representation to enhance the HRI experience. The robot’s behaviors must be modified by humans, directly or indirectly. In this paper, we integrate our human representation framework in a cognitive architecture to allow that people who interact with the robot could modify its behavior, not only with the interaction but also with their culture or the social context. The human representation framework represents and distributes the proxemic zones’ information in a standard way, through a cost map. We have evaluated the influence of the decision-making system in human-aware navigation and how a local planner may be decisive in this navigation. The material developed during this research can be found in a public repository (https://github.com/IntelligentRoboticsLabs/social_navigation2_WAF) and instructions to facilitate the reproducibility of the results.S

    Understanding Interactions for Smart Wheelchair Navigation in Crowds

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    A Review of Verbal and Non-Verbal Human-Robot Interactive Communication

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    In this paper, an overview of human-robot interactive communication is presented, covering verbal as well as non-verbal aspects of human-robot interaction. Following a historical introduction, and motivation towards fluid human-robot communication, ten desiderata are proposed, which provide an organizational axis both of recent as well as of future research on human-robot communication. Then, the ten desiderata are examined in detail, culminating to a unifying discussion, and a forward-looking conclusion

    Temporal models of motions and forces for Human-Robot Interactive manipulation

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    L'intĂ©rĂȘt pour la robotique a dĂ©butĂ© dans les annĂ©es 70 et depuis les robots n'ont cessĂ© de remplacer les humains dans l'industrie. L'automatisation Ă  outrance n'apporte cependant pas que des avantages, car elle nĂ©cessite des environnements parfaitement contrĂŽlĂ©s et la reprogrammation d'une tĂąche est longue et fastidieuse. Le besoin accru d'adaptabilitĂ© et de rĂ©-utilisabilitĂ© des systĂšmes d'assemblage force la robotique Ă  se rĂ©volutionner en amenant notamment l'homme et le robot Ă  interagir. Ce nouveau type de collaboration permet de combiner les forces respectives des humains et des robots. Cependant l'homme ne pourra ĂȘtre inclus en tant qu'agent actif dans ces nouveaux espaces de travail collaboratifs que si l'on dispose de robots sĂ»rs, intuitifs et facilement reprogrammables. C'est Ă  la lumiĂšre de ce constat qu'on peut deviner le rĂŽle crucial de la gĂ©nĂ©ration de mouvement pour les robots de demain. Pour que les humains et les robots puissent collaborer, ces derniers doivent gĂ©nĂ©rer des mouvements sĂ»rs afin de garantir la sĂ©curitĂ© de l'homme tant physique que psychologique. Les trajectoires sont un excellent modĂšle pour la gĂ©nĂ©ration de mouvements adaptĂ©s aux robots collaboratifs, car elles offrent une description simple et prĂ©cise de l'Ă©volution du mouvement. Les trajectoires dĂźtes souples sont bien connues pour gĂ©nĂ©rer des mouvements sĂ»rs et confortables pour l'homme. Dans cette thĂšse nous proposons un algorithme de gĂ©nĂ©ration de trajectoires temps-rĂ©el basĂ© sur des sĂ©quences de segments de fonctions polynomiales de degrĂ© trois pour construire des trajectoires souples. Ces trajectoires sont construites Ă  partir de conditions initiales et finales arbitraires, une condition nĂ©cessaire pour que les robots soient capables de rĂ©agir instantanĂ©ment Ă  des Ă©vĂ©nements imprĂ©vus. L'approche basĂ©e sur un modĂšle Ă  jerk-contraint offre des solutions orientĂ©es performance: les trajectoires sont optimales en temps sous contraintes de sĂ©curitĂ©. Ces contraintes de sĂ©curitĂ© sont des contraintes cinĂ©matiques qui dĂ©pendent de la tĂąche et du contexte et doivent ĂȘtre spĂ©cifiĂ©es. Pour guider le choix de ces contraintes, nous avons Ă©tudiĂ© le rĂŽle de la cinĂ©matique dans la dĂ©finition des propriĂ©tĂ©s ergonomiques du mouvement. L'algorithme a Ă©galement Ă©tĂ© Ă©tendu pour accepter des configurations initiales non admissibles permettant la gĂ©nĂ©ration de trajectoires sous contraintes cinĂ©matiques non constantes. Cette extension est essentielle dans le contexte des interactions physiques homme-robot, car le robot doit ĂȘtre capable d'adapter son comportement en temps-rĂ©el pour prĂ©server la sĂ©curitĂ© physique et psychologique des humains. Cependant considĂ©rer le problĂšme de la gĂ©nĂ©ration de trajectoires ne suffit pas si on ne considĂšre pas le contrĂŽle. Le passage d'une trajectoire Ă  une autre est un problĂšme difficile pour la plupart des systĂšmes robotiques dans des contextes applicatifs rĂ©els. Pour cela, nous proposons une stratĂ©gie de contrĂŽle rĂ©actif de ces trajectoires ainsi qu'une architecture construite autour de l'utilisation des trajectoires.It was in the 70s when the interest for robotics really emerged. It was barely half a century ago, and since then robots have been replacing humans in the industry. This robot-oriented solution doesn't come without drawbacks as full automation requires time-consuming programming as well as rigid environments. With the increased need for adaptability and reusability of assembly systems, robotics is undergoing major changes and see the emergence of a new type of collaboration between humans and robots. Human-Robot collaboration get the best of both world by combining the respective strengths of humans and robots. But, to include the human as an active agent in these new collaborative workspaces, safe and flexible robots are required. It is in this context that we can apprehend the crucial role of motion generation in tomorrow's robotics. For the emergence of human-robot cooperation, robots have to generate motions ensuring the safety of humans, both physical and physchological. For this reason motion generation has been a restricting factor to the growth of robotics in the past. Trajectories are excellent candidates in the making of desirable motions designed for collaborative robots, because they allow to simply and precisely describe the motions. Smooth trajectories are well known to provide safe motions with good ergonomic properties. In this thesis we propose an Online Trajectory Generation algorithm based on sequences of segment of third degree polynomial functions to build smooth trajectories. These trajectories are built from arbitrary initial and final conditions, a requirement for robots to be able to react instantaneously to unforeseen events. Our approach built on a constrained-jerk model offers performance-oriented solutions : the trajectories are time-optimal under safety constraints. These safety constraints are kinematic constraints that are task and context dependent and must be specified. To guide the choice of these constraints we investigated the role of kinematics in the definition of ergonomics properties of motions. We also extended our algorithm to cope with non-admissible initial configurations, opening the way to trajectory generation under non-constant motion constraints. This feature is essential in the context of physical Human-Robot Interactions, as the robot must adapt its behavior in real time to preserve both the physical and psychological safety of humans. However, only considering the trajectory generation problem is not enough and the control of these trajectories must be adressed. Switching from a trajectory to another is a difficult problem for most robotic systems in real applicative contexts. For this purpose we propose a strategy for the Reactive Control of these Trajectories as well as an architecture built around the use of trajectories
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