353 research outputs found
Inclusion of service robots in the daily lives of frail older users: a step-by-step definition procedure on users' requirements
The implications for the inclusion of robots in the daily lives of frail older adults, especially in relation to these population needs, have not been extensively studied. The âMulti-Role Shadow Robotic System for Independent Livingâ (SRS) project has developed a remotelycontrolled, semi-autonomous robotic system to be used in domestic environments. The objective of this paper is to document the iterative procedure used to identify, select and prioritize user requirements. Seventy-four requirements were identified by means of focus
groups, individual interviews and scenario-based interviews. The list of user requirements, ordered according to impact, number and transnational criteria, revealed a high number of requirements related to basic and instrumental activities of daily living, cognitive and social support and monitorization, and also involving privacy, safety and adaptation issues. Analysing and understanding older usersâ perceptions and needs when interacting with technological devices adds value to assistive technology and ensures that the systems address currently unmet needs
User-centered design of a dynamic-autonomy remote interaction concept for manipulation-capable robots to assist elderly people in the home
In this article, we describe the development of a human-robot interaction concept for service robots to assist elderly people in the home with physical tasks. Our approach is based on the insight that robots are not yet able to handle all tasks autonomously with sufficient reliability in the complex and heterogeneous environments of private homes. We therefore employ remote human operators to assist on tasks a robot cannot handle completely autonomously. Our development methodology was user-centric and iterative, with six user studies carried out at various stages involving a total of 241 participants. The concept is under implementation on the Care-O-bot 3 robotic platform. The main contributions of this article are (1) the results of a survey in form of a ranking of the demands of elderly people and informal caregivers for a range of 25 robot services, (2) the results of an ethnography investigating the suitability of emergency teleassistance and telemedical centers for incorporating robotic teleassistance, and (3) a user-validated human-robot interaction concept with three user roles and corresponding three user interfaces designed as a solution to the problem of engineering reliable service robots for home environments
Fuzzy optimisation based symbolic grounding for service robots
A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophySymbolic grounding is a bridge between task level planning and actual robot sensing and actuation. Uncertainties raised by unstructured environments make a bottleneck for integrating traditional artificial intelligence with service robotics. In this research, a fuzzy optimisation based symbolic grounding approach is presented. This approach can handle uncertainties and helps service robots to determine the most comfortable base region for grasping objects in a fetch and carry task. Novel techniques are applied to establish fuzzy objective function, to model fuzzy constraints and to perform fuzzy optimisation. The approach does not have the short comings of othersâ work and the computation time is dramatically reduced in compare with other methods. The advantages of the proposed fuzzy optimisation based approach are evidenced by experiments that were undertaken in Care-O-bot 3 (COB 3) and Robot Operating System (ROS) platforms
Engineering evolutionary control for real-world robotic systems
Evolutionary Robotics (ER) is the field of study concerned with the application
of evolutionary computation to the design of robotic systems. Two main
issues have prevented ER from being applied to real-world tasks, namely scaling to
complex tasks and the transfer of control to real-robot systems. Finding solutions
to complex tasks is challenging for evolutionary approaches due to the bootstrap
problem and deception. When the task goal is too difficult, the evolutionary process
will drift in regions of the search space with equally low levels of performance
and therefore fail to bootstrap. Furthermore, the search space tends to get rugged
(deceptive) as task complexity increases, which can lead to premature convergence.
Another prominent issue in ER is the reality gap. Behavioral control is typically
evolved in simulation and then only transferred to the real robotic hardware when
a good solution has been found. Since simulation is an abstraction of the real
world, the accuracy of the robot model and its interactions with the environment
is limited. As a result, control evolved in a simulator tends to display a lower
performance in reality than in simulation.
In this thesis, we present a hierarchical control synthesis approach that enables
the use of ER techniques for complex tasks in real robotic hardware by mitigating
the bootstrap problem, deception, and the reality gap. We recursively decompose
a task into sub-tasks, and synthesize control for each sub-task. The individual
behaviors are then composed hierarchically. The possibility of incrementally
transferring control as the controller is composed allows transferability issues to
be addressed locally in the controller hierarchy. Our approach features hybridity,
allowing different control synthesis techniques to be combined. We demonstrate
our approach in a series of tasks that go beyond the complexity of tasks where ER
has been successfully applied. We further show that hierarchical control can be applied
in single-robot systems and in multirobot systems. Given our long-term goal
of enabling the application of ER techniques to real-world tasks, we systematically
validate our approach in real robotic hardware. For one of the demonstrations in
this thesis, we have designed and built a swarm robotic platform, and we show the
first successful transfer of evolved and hierarchical control to a swarm of robots
outside of controlled laboratory conditions.A Robótica Evolutiva (RE) é a årea de investigação que estuda a aplicação de
computação evolutiva na conceção de sistemas robóticos. Dois principais desafios
tĂȘm impedido a aplicação da RE em tarefas do mundo real: a dificuldade em solucionar
tarefas complexas e a transferĂȘncia de controladores evoluĂdos para sistemas
robóticos reais. Encontrar soluçÔes para tarefas complexas é desafiante para as
técnicas evolutivas devido ao bootstrap problem e à deception. Quando o objetivo
Ă© demasiado difĂcil, o processo evolutivo tende a permanecer em regiĂ”es do espaço
de procura com nĂveis de desempenho igualmente baixos, e consequentemente nĂŁo
consegue inicializar. Por outro lado, o espaço de procura tende a enrugar à medida
que a complexidade da tarefa aumenta, o que pode resultar numa convergĂȘncia
prematura. Outro desafio na RE Ă© a reality gap. O controlo robĂłtico Ă© tipicamente
evoluĂdo em simulação, e sĂł Ă© transferido para o sistema robĂłtico real quando uma
boa solução tiver sido encontrada. Como a simulação é uma abstração da realidade,
a precisão do modelo do robÎ e das suas interaçÔes com o ambiente é limitada,
podendo resultar em controladores com um menor desempenho no mundo real.
Nesta tese, apresentamos uma abordagem de sĂntese de controlo hierĂĄrquica
que permite o uso de técnicas de RE em tarefas complexas com hardware robótico
real, mitigando o bootstrap problem, a deception e a reality gap. Decompomos
recursivamente uma tarefa em sub-tarefas, e sintetizamos controlo para cada subtarefa.
Os comportamentos individuais sĂŁo entĂŁo compostos hierarquicamente.
A possibilidade de transferir o controlo incrementalmente Ă medida que o controlador
é composto permite que problemas de transferibilidade possam ser endereçados
localmente na hierarquia do controlador. A nossa abordagem permite
o uso de diferentes tĂ©cnicas de sĂntese de controlo, resultando em controladores
hĂbridos. Demonstramos a nossa abordagem em vĂĄrias tarefas que vĂŁo para alĂ©m
da complexidade das tarefas onde a RE foi aplicada. Também mostramos que o
controlo hierĂĄrquico pode ser aplicado em sistemas de um robĂŽ ou sistemas multirobĂŽ.
Dado o nosso objetivo de longo prazo de permitir o uso de técnicas de
RE em tarefas no mundo real, concebemos e desenvolvemos uma plataforma de
robĂłtica de enxame, e mostramos a primeira transferĂȘncia de controlo evoluĂdo e
hierårquico para um exame de robÎs fora de condiçÔes controladas de laboratório.This work has been supported by the Portuguese Foundation for Science
and Technology (Fundação para a CiĂȘncia e Tecnologia) under the grants
SFRH/BD/76438/2011, EXPL/EEI-AUT/0329/2013, and by Instituto de TelecomunicaçÔes
under the grant UID/EEA/50008/2013
Building and Designing Expressive Speech Synthesis
We know there is something special about speech. Our voices are not just a means of communicating. They also give a deep impression of who we are and what we might know. They can betray our upbringing, our emotional state, our state of health. They can be used to persuade and convince, to calm and to excite. As speech systems enter the social domain they are required to interact, support and mediate our social relationships with 1) each other, 2) with digital information, and, increasingly, 3) with AI-based algorithms and processes. Socially Interactive Agents (SIAs) are at the fore- front of research and innovation in this area. There is an assumption that in the future âspoken language will provide a natural conversational interface between human beings and so-called intelligent systems.â [Moore 2017, p. 283]. A considerable amount of previous research work has tested this assumption with mixed results. However, as pointed out âvoice interfaces have become notorious for fostering frustration and failureâ [Nass and Brave 2005, p.6]. It is within this context, between our exceptional and intelligent human use of speech to communicate and interact with other humans, and our desire to leverage this means of communication for artificial systems, that the technology, often termed expressive speech synthesis uncomfortably falls. Uncomfortably, because it is often overshadowed by issues in interactivity and the underlying intelligence of the system which is something that emerges from the interaction of many of the components in a SIA. This is especially true of what we might term conversational speech, where decoupling how things are spoken, from when and to whom they are spoken, can seem an impossible task. This is an even greater challenge in evaluation and in characterising full systems which have made use of expressive speech. Furthermore when designing an interaction with a SIA, we must not only consider how SIAs should speak but how much, and whether they should even speak at all. These considerations cannot be ignored. Any speech synthesis that is used in the context of an artificial agent will have a perceived accent, a vocal style, an underlying emotion and an intonational model. Dimensions like accent and personality (cross speaker parameters) as well as vocal style, emotion and intonation during an interaction (within-speaker parameters) need to be built in the design of a synthetic voice. Even a default or neutral voice has to consider these same expressive speech synthesis components. Such design parameters have a strong influence on how effectively a system will interact, how it is perceived and its assumed ability to perform a task or function. To ignore these is to blindly accept a set of design decisions that ignores the complex effect speech has on the userâs successful interaction with a system. Thus expressive speech synthesis is a key design component in SIAs. This chapter explores the world of expressive speech synthesis, aiming to act as a starting point for those interested in the design, building and evaluation of such artificial speech. The debates and literature within this topic are vast and are fundamentally multidisciplinary in focus, covering a wide range of disciplines such as linguistics, pragmatics, psychology, speech and language technology, robotics and human-computer interaction (HCI), to name a few. It is not our aim to synthesise these areas but to give a scaffold and a starting point for the reader by exploring the critical dimensions and decisions they may need to consider when choosing to use expressive speech. To do this, the chapter explores the building of expressive synthesis, highlighting key decisions and parameters as well as emphasising future challenges in expressive speech research and development. Yet, before these are expanded upon we must first try and define what we actually mean by expressive speech
Advanced Automation for Space Missions
The feasibility of using machine intelligence, including automation and robotics, in future space missions was studied
Agent Based Software Testing for Multi Agent Systems
Software testing starts with verification and validation and fulfills the requirement of the customer. Testing can be done by automation tool like Win runner, QTP or manually. If we talk about manual testing it takes lot of time and manpower also so nowadays we are using automation software. When we talk about automation testing so the cost of such kind of testing is very high so each company cannot afford. In this paper we are presenting agent based testing which is helpful for both kind of testing. Multi-Agent Systems (MAS) are characterized by autonomous and collaborative behaviors [1, 2]. Developing such systems is a complex process. As a result, a methodology for developing MAS is highly necessary. In this paper, a methodology using roles and ontology for such a purpose is presented [2]. The functionality of roles is estimated in the various phases of the MAS development. It is based on an emphasis on the properties and behaviors associated with each agent in MAS
Machine Learning Meets Advanced Robotic Manipulation
Automated industries lead to high quality production, lower manufacturing
cost and better utilization of human resources. Robotic manipulator arms have
major role in the automation process. However, for complex manipulation tasks,
hard coding efficient and safe trajectories is challenging and time consuming.
Machine learning methods have the potential to learn such controllers based on
expert demonstrations. Despite promising advances, better approaches must be
developed to improve safety, reliability, and efficiency of ML methods in both
training and deployment phases. This survey aims to review cutting edge
technologies and recent trends on ML methods applied to real-world manipulation
tasks. After reviewing the related background on ML, the rest of the paper is
devoted to ML applications in different domains such as industry, healthcare,
agriculture, space, military, and search and rescue. The paper is closed with
important research directions for future works
A multi-modal perception based assistive robotic system for the elderly
Edited by Giovanni Maria Farinella, Takeo Kanade, Marco Leo, Gerard G. Medioni, Mohan TrivediInternational audienceIn this paper, we present a multi-modal perception based framework to realize a non-intrusive domestic assistive robotic system. It is non-intrusive in that it only starts interaction with a user when it detects the user's intention to do so. All the robot's actions are based on multi-modal perceptions which include user detection based on RGB-D data, user's intention-for-interaction detection with RGB-D and audio data, and communication via user distance mediated speech recognition. The utilization of multi-modal cues in different parts of the robotic activity paves the way to successful robotic runs (94% success rate). Each presented perceptual component is systematically evaluated using appropriate dataset and evaluation metrics. Finally the complete system is fully integrated on the PR2 robotic platform and validated through system sanity check runs and user studies with the help of 17 volunteer elderly participants
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