1,721,079 research outputs found

    A Scalable Framework for Multi-Robot Tele-Impedance Control

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    In this article, we present an online scalable tele-impedance framework, which enables the individual and collaborative control of multiple different robotic platforms. The framework provides an intuitive low-cost interface with visual feedback and a SpaceMouse, through which the operator can define the desired task-level trajectories and impedance profiles. With a simple mouse click, the user can switch between the robots and the collaborative operation mode. The control, subsequently, manages the distribution of the required parameters into the involved robots. Thanks to the introduced virtual hand concept, where each robot is defined as a finger, new robots can be easily added or removed via their kinodynamic parameters. The proposed framework was evaluated with three different experiments: a simulated auscultation on a mock-up patient, a cooperative task where a robot drives the patient on a wheelchair and a different robot performs the auscultation, and a collaborative task where two robots relocate a container. The results demonstrate the capabilities of the framework in terms of adaptability to different robotic platforms, the number of robots involved, and the task requirements. Additionally, quantitative and subjective analysis of 12 subjects showed how the developed interface, even in the presence of inaccurate visual feedback, allowed a smooth and accurate execution of the tasks

    A Reconfigurable Interface for Ergonomic and Dynamic Tele-Locomanipulation

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    Prolonged remote tele-locomanipulation of multi degrees-of-freedom mobile manipulators requires a compromise between the system's performance and the operator's ergonomics. Neglecting this demand can significantly affect either the task completion or the level of comfort to achieve it. However, the simultaneous consideration of these key factors has received less attention in the literature. To respond to this demand, in this work, we introduce a new teleoperation setup, which integrates the features of an ergonomic and a highly maneuverable interface into a unified solution. The ergonomic part of the interface implements a 3D mouse-like functionality, enabling the execution of long navigation tasks for the floating base. The highly manoeuvrable interface instead, enables the operator to perform dynamic or more precise manipulation by moving his/her arm in space. The locomotion and manipulation modes of the follower robot are controlled separately, which can be easily and seamlessly switched by the operator by pressing a button at any moment. Furthermore, due to the follower manipulator's redundancy, this robot is controlled by a hierarchical quadratic programming technique which enables the definition of a set of secondary tasks to be executed in the robot's nullspace. Finally, to demonstrate the advantages and disadvantages of the proposed user interfaces, five participants are asked to perform two different experiments: (i) target selection task on a moving surface and (ii) remote path tracking on a fixed surface. The quantitative and qualitative analyses show the effectiveness of the proposed interface during the teleoperation tasks, especially when it comes to the precise and dynamic task execution

    Impact Planning and Pre-configuration based on Hierarchical Quadratic Programming

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    Impacts and other non-smooth behaviors are usually unwanted in robotic applications. However, several industrial tasks such as deburring, removing excess material, and assembling/fitting, involve impacts between objects, which can benefit from robotic automation due to the risks posed to human health. Towards this objective, in this paper, we propose a method for optimal impact planning and pre-configuration for torque-controlled robots. We thus employ a well-known impulsive contact model to plan the impact force and create a hierarchical quadratic programming based controller capable of minimizing the robot's peak torques by reconfiguring its joints optimally, before the impact occurs. The results obtained from multiple experiments during an industrial deburring task are discussed. Using a 7-DoF manipulator, we show consistent results, both in terms of accuracy of the impact force tracking with respect to the desired forces, and in terms of peak torques reduction and uniform torques distribution

    A Shared-Autonomy Approach to Goal Detection and Navigation Control of Mobile Collaborative Robots

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    Autonomous goal detection and navigation control of mobile robots in remote environments can help to unload human operators from simple, monotonous tasks allowing them to focus on more cognitively stimulating actions. This can result in better task performances, while creating user-interfaces that are understandable by non-experts. However, full autonomy in unpredictable and dynamically changing environments is still far from becoming a reality. Thus, teleoperated systems integrating the supervisory role and instantaneous decision-making capacity of humans are still required for fast and reliable robotic operations. This work presents a novel shared-autonomy framework for goal detection and navigation control of mobile manipulators. The controller exploits human-gaze information to estimate the desired goal. This is used together with control-pad data to predict user intention, and to activate the autonomous control for executing a target task. Using the control-pad device, a user can react to unexpected disturbances and halt the autonomous mode at any time. By releasing the control-pad device (e.g., after avoiding an instantaneous obstacle) the controller smoothly switches back to the autonomous mode and navigates the robot towards the target. Experiments for reaching a target goal in the presence of unknown obstacles are carried out to evaluate the performance of the proposed shared-autonomy framework over seven subjects. The results prove the accuracy, time-efficiency, and ease-of-use of the presented shared-autonomy control framework

    A probabilistic shared-control framework for mobile robots

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    Full teleoperation of mobile robots during the execution of complex tasks not only demands high cognitive and physical effort but also generates less optimal trajectories compared to autonomous controllers. However, the use of the latter in cluttered and dynamically varying environments is still an open and challenging topic. This is due to several factors such as sensory measurement failures and rapid changes in task requirements. Shared-control approaches have been introduced to overcome these issues. However, these either present a strong decoupling that makes them still sensitive to unexpected events, or highly complex interfaces only accessible to expert users. In this work, we focus on the development of a novel and intuitive shared-control framework for target detection and control of mobile robots. The proposed framework merges the information coming from a teleoperation device with a stochastic evaluation of the desired goal to generate autonomous trajectories while keeping a human-in-control approach. This allows the operator to react in case of goal changes, sensor failures, or unexpected disturbances. The proposed approach is validated through several experiments both in simulation and in a real environment where the users try to reach a chosen goal in the presence of obstacles and unexpected disturbances. Operators receive both visual feedback of the environment and voice feedback of the goal estimation status while teleoperating a mobile robot through a control-pad. Results of the proposed method are compared to pure teleoperation proving a better time-efficiency and easiness-of-use of the presented approach

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods
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