1,720,964 research outputs found
A Unified Approach for Virtual Fixtures and Goal-Driven Variable Admittance Control in Manual Guidance Applications
No full textIn applications of human-robot physical interaction, it is important to guarantee high accuracy not only in terms of the position of the end-effector, but also in terms of its orientation. While translational movements are easily understandable for a human, rotational ones do not have an immediate interpretation. This does not allow the operator to achieve an adequate positioning accuracy when a target orientation is set. In this work, a suitable strategy that facilitates the human in accomplishing rotational motion is proposed through the formulation of rotational virtual fixtures. This is obtained thanks to a clever description of the orientation that allows to draw an equivalence between the formulation of translational virtual fixtures and their rotational counterparts. To further improve the human comprehension of the best motion direction in the rotational world, a variable admittance control is also designed. We finally propose to jointly exploit these techniques to achieve the best possible performance in terms of positioning accuracy. The performance are evaluated by means of rotational point to point cooperative motions involving several subjects and an ABB IRB-140 robot
Goal-driven variable admittance control for robot manual guidance
No full textIn this paper we address variable admittance control for human-robot physical interaction in manual guidance applications. In the proposed solution, the parameters of the admittance filter can change not only as a function of the current state of motion (i.e. whether the human guiding the robot ia accelerating or decelerating) but also with reference to a predefined goal position. The human is in fact gently guided towards the goal along some curved paths, where the damping is conveniently scaled in order to accommodate the motion towards the goal position. The algorithm also allows the human to reach goals that he/she cannot directly see because for example the transported object is bulky and obstructs the worker view. The performance of the proposed controller are evaluated by means of point to point cooperative motions with multiple volunteers using an ABB IRB140 robot
Identification of Robot Forward Dynamics via Neural Network
No full textIn recent years machine learning techniques have received an increasing interest, since they can be successfully applied to several application domains, among which robotics. In this field, neural networks can be used to approximate the dynamic model of the manipulator, which is highly non-linear and often affected by some uncertainties regarding the dynamic parameters. These parameters are typically not provided by the manufacturer or partially unknown. In this work, we propose the use of neural networks to perform the black-box identification of the robot forward dynamics. This consists in performing a one step ahead prediction of the robot joint positions, velocities and accelerations based on the knowledge of the joint positions, velocities at the previous time step and the actuation torques. To this purpose, we analyzed both static and dynamic neural networks structures with different combinations of hyper-parameters. We tested the performance by comparing the predicted output with both simulated data and those acquired on a real industrial manipulator, ABB IRB 140
Human intention estimation and goal-driven variable admittance control in manual guidance applications
No full textIn collaborative robotics, and especially in physical human-robot interaction, the prediction of the human motion intention can strongly improve the effectiveness of the synergy. This work tackles the issue of estimating the most likely final target towards which the operator is guiding the end-effector of the manipulator to actively assist him/her in accomplishing the task. A novel inference algorithm, based on Bayesian statistics, has been developed. It predicts the most likely 3D target among a predefined set and it also takes into account the possibility that the human drives the robot towards an unknown target. Then, a variable admittance control has also been conceived. It suitably adapts its parameters to establish a directional haptic feedback that helps the human accurately reach the desired goal position. The proposed strategies allow the human to precisely reach the goal even when his/her view is obstructed by the transported object. These algorithms have been validated through point to point collaborative motions with several volunteers and an ABB IRB140 robot
RRT∗ and Goal-Driven Variable Admittance Control for Obstacle Avoidance in Manual Guidance Applications
No full textIn manual guidance robotic applications, like the handling of large and heavy objects in a cluttered environment, it is important to guarantee that the operator accurately reaches the goal position without collisions with working isles or other obstacles in the surrounding environment. When the transported object is bulky, the operator's view is obstructed and the situation becomes more critical. In this work, a novel variable admittance control provides the operator with a directional haptic feedback about the best motion direction towards the goal. This feedback allows the user to accurately reach the target position in a cluttered environment, also in case his/her view is partially or totally obstructed. To select the best motion direction in a cluttered workspace, a tree-based structure rooted in the goal is optimally built offline to fully explore the environment free-space based on the workspace layout and regardless of the initial position. Then, at each time instant, the optimal motion direction is determined based on the current position with respect to the exploring structure and on the user motion intention. In this work, to build the tree structure, we adapt RRT∗ algorithm to the manual guidance context and we define a tailored cost function. The performance is evaluated in many scenarios with a variable number of obstacles of different shapes involving several subjects and a Comau Smart Six robot
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Full text linkWe 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
Full text linkWe 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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