2,027 research outputs found

    INVESTIGATION OF INDUSTRY 5.0 HURDLES AND THEIR MITIGATION TACTICS IN EMERGING ECONOMIES BY TODIM ARITHMETIC AND GEOMETRIC AGGREGATION OPERATORS IN SINGLE VALUE NEUTROSOPHIC ENVIRONMENT

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    Industry 5.0 acceptance is accelerating, but research is still in its infancy, and existing research covers a small subset of context-specific obstacles. This study aims to enumerate all potential obstacles, quantitatively rank them, and assess interdependencies at the organizational level for Industry 5.0 adoption. To achieve this, we thoroughly review the literature, identify obstacles, and investigate causal relationships using a multi-criteria decision-making approach called single value Neutrosophic TODIM. Single-valued Neutrosophic sets (SVNS) ensembles are employed in a real-world setting to deal with uncertainty and indeterminacy. The suggested strategy enables the experts to conduct group decision-making by focusing on ranking the smaller collection of criterion values and the comparison with the decision-making trial and evaluation laboratory method (DEMATEL). According to the findings, the most significant hurdles are expenses and the funding system, capacity scalability, upskilling, and reskilling of human labor. As a result, a comfortable atmosphere is produced for decision-making, enabling the experts to handle an acceptable amount of data while still making choices

    Human-robot Interaction For Multi-robot Systems

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    Designing an effective human-robot interaction paradigm is particularly important for complex tasks such as multi-robot manipulation that require the human and robot to work together in a tightly coupled fashion. Although increasing the number of robots can expand the area that the robots can cover within a bounded period of time, a poor human-robot interface will ultimately compromise the performance of the team of robots. However, introducing a human operator to the team of robots, does not automatically improve performance due to the difficulty of teleoperating mobile robots with manipulators. The human operator’s concentration is divided not only among multiple robots but also between controlling each robot’s base and arm. This complexity substantially increases the potential neglect time, since the operator’s inability to effectively attend to each robot during a critical phase of the task leads to a significant degradation in task performance. There are several proven paradigms for increasing the efficacy of human-robot interaction: 1) multimodal interfaces in which the user controls the robots using voice and gesture; 2) configurable interfaces which allow the user to create new commands by demonstrating them; 3) adaptive interfaces which reduce the operator’s workload as necessary through increasing robot autonomy. This dissertation presents an evaluation of the relative benefits of different types of user interfaces for multi-robot systems composed of robots with wheeled bases and three degree of freedom arms. It describes a design for constructing low-cost multi-robot manipulation systems from off the shelf parts. User expertise was measured along three axes (navigation, manipulation, and coordination), and participants who performed above threshold on two out of three dimensions on a calibration task were rated as expert. Our experiments reveal that the relative expertise of the user was the key determinant of the best performing interface paradigm for that user, indicating that good user modiii eling is essential for designing a human-robot interaction system that will be used for an extended period of time. The contributions of the dissertation include: 1) a model for detecting operator distraction from robot motion trajectories; 2) adjustable autonomy paradigms for reducing operator workload; 3) a method for creating coordinated multi-robot behaviors from demonstrations with a single robot; 4) a user modeling approach for identifying expert-novice differences from short teleoperation traces

    Bridging distances in technology and regulation

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    Multimodal Shared-Control Interaction for Mobile Robots in AAL Environments

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    This dissertation investigates the design, development and implementation of cognitively adequate, safe and robust, spatially-related, multimodal interaction between human operators and mobile robots in Ambient Assisted Living environments both from the theoretical and practical perspectives. By focusing on different aspects of the concept Interaction, the essential contribution of this dissertation is divided into three main research packages; namely, Formal Interaction, Spatial Interaction and Multimodal Interaction in AAL. As the principle package, in Formal Interaction, research effort is dedicated to developing a formal language based interaction modelling and management solution process and a unified dialogue modelling approach. This package aims to enable a robust, flexible, and context-sensitive, yet formally controllable and tractable interaction. This type of interaction can be used to support the interaction management of any complex interactive systems, including the ones covered in the other two research packages. In the second research package, Spatial Interaction, a general qualitative spatial knowledge based multi-level conceptual model is developed and proposed. The goal is to support a spatially-related interaction in human-robot collaborative navigation. With a model-based computational framework, the proposed conceptual model has been implemented and integrated into a practical interactive system which has been evaluated by empirical studies. It has been particularly tested with respect to a set of high-level and model-based conceptual strategies for resolving the frequent spatially-related communication problems in human-robot interaction. Last but not least, in Multimodal Interaction in AAL, attention is drawn to design, development and implementation of multimodal interaction for elderly persons. In this elderly-friendly scenario, ageing-related characteristics are carefully considered for an effective and efficient interaction. Moreover, a standard model based empirical framework for evaluating multimodal interaction is provided. This framework was especially applied to evaluate a minutely developed and systematically improved elderly-friendly multimodal interactive system through a series of empirical studies with groups of elderly persons

    Studies on user control in ambient intelligent systems

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    People have a deeply rooted need to experience control and be effective in interactions with their environments. At present times, we are surrounded by intelligent systems that take decisions and perform actions for us. This should make life easier, but there is a risk that users experience less control and reject the system. The central question in this thesis is whether we can design intelligent systems that have a degree of autonomy, while users maintain a sense of control. We try to achieve this by giving the intelligent system an 'expressive interface’: the part that provides information to the user about the internal state, intentions and actions of the system. We examine this question both in the home and the work environment.We find the notion of a ‘system personality’ useful as a guiding principle for designing interactions with intelligent systems, for domestic robots as well as in building automation. Although the desired system personality varies per application, in both domains a recognizable system personality can be designed through expressive interfaces using motion, light, sound, and social cues. The various studies show that the level of automation and the expressive interface can influence the perceived system personality, the perceived level of control, and user’s satisfaction with the system. This thesis shows the potential of the expressive interface as an instrument to help users understand what is going on inside the system and to experience control, which might be essential for the successful adoption of the intelligent systems of the future.<br/

    Attention-controlled acquisition of a qualitative scene model for mobile robots

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    Haasch A. Attention-controlled acquisition of a qualitative scene model for mobile robots. Bielefeld (Germany): Bielefeld University; 2007.Robots that are used to support humans in dangerous environments, e.g., in manufacture facilities, are established for decades. Now, a new generation of service robots is focus of current research and about to be introduced. These intelligent service robots are intended to support humans in everyday life. To achieve a most comfortable human-robot interaction with non-expert users it is, thus, imperative for the acceptance of such robots to provide interaction interfaces that we humans are accustomed to in comparison to human-human communication. Consequently, intuitive modalities like gestures or spontaneous speech are needed to teach the robot previously unknown objects and locations. Then, the robot can be entrusted with tasks like fetch-and-carry orders even without an extensive training of the user. In this context, this dissertation introduces the multimodal Object Attention System which offers a flexible integration of common interaction modalities in combination with state-of-the-art image and speech processing techniques from other research projects. To prove the feasibility of the approach the presented Object Attention System has successfully been integrated in different robotic hardware. In particular, the mobile robot BIRON and the anthropomorphic robot BARTHOC of the Applied Computer Science Group at Bielefeld University. Concluding, the aim of this work, to acquire a qualitative Scene Model by a modular component offering object attention mechanisms, has been successfully achieved as demonstrated on numerous occasions like reviews for the EU-integrated Project COGNIRON or demos

    Hybrid Cloud Model Checking Using the Interaction Layer of HARMS for Ambient Intelligent Systems

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    Soon, humans will be co-living and taking advantage of the help of multi-agent systems in a broader way than the present. Such systems will involve machines or devices of any variety, including robots. These kind of solutions will adapt to the special needs of each individual. However, to the concern of this research effort, systems like the ones mentioned above might encounter situations that will not be seen before execution time. It is understood that there are two possible outcomes that could materialize; either keep working without corrective measures, which could lead to an entirely different end or completely stop working. Both results should be avoided, specially in cases where the end user will depend on a high level guidance provided by the system, such as in ambient intelligence applications. This dissertation worked towards two specific goals. First, to assure that the system will always work, independently of which of the agents performs the different tasks needed to accomplish a bigger objective. Second, to provide initial steps towards autonomous survivable systems which can change their future actions in order to achieve the original final goals. Therefore, the use of the third layer of the HARMS model was proposed to insure the indistinguishability of the actors accomplishing each task and sub-task without regard of the intrinsic complexity of the activity. Additionally, a framework was proposed using model checking methodology during run-time for providing possible solutions to issues encountered in execution time, as a part of the survivability feature of the systems final goals
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