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Fabio Ruggiero

Bio: Fabio Ruggiero is an academic researcher from University of Naples Federico II. The author has contributed to research in topics: Control theory & Computer science. The author has an hindex of 17, co-authored 69 publications receiving 1397 citations. Previous affiliations of Fabio Ruggiero include Information Technology University & CINVESTAV.


Papers
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Journal ArticleDOI
21 Feb 2018
TL;DR: This letter tries to collect the results reached by the research community so far within the field of aerial manipulation, especially from the technological and control point of view.
Abstract: Aerial manipulation aims at combining the versatility and the agility of some aerial platforms with the manipulation capabilities of robotic arms. This letter tries to collect the results reached by the research community so far within the field of aerial manipulation, especially from the technological and control point of view. A brief literature review of general aerial robotics and space manipulation is carried out as well.

339 citations

Journal ArticleDOI
TL;DR: A Cartesian impedance control, which provides a dynamic relationship between external generalized forces acting on the structure and the system motion, is designed and tested in a simulated case study.

147 citations

Proceedings ArticleDOI
26 May 2015
TL;DR: A multilayer architecture to control multirotor UAVs equipped with a servo robot arm is proposed in this paper to control the aerial platform taking into account the presence of the moving manipulator.
Abstract: A multilayer architecture to control multirotor UAVs equipped with a servo robot arm is proposed in this paper. The main purpose is to control the aerial platform taking into account the presence of the moving manipulator. Three layers are considered in this work. First, a novel mechanism is proposed considering a moving battery to counterweight the statics of the robotic arm. Then, in order to overcome the mechanical limitations of the previous layer, the residual of the arm static effects on the UAV is computed and compensated through the given control thrust and torques. Finally, an estimator of external forces and moments acting on the aerial vehicle is considered and the estimations are fed back to the controller to compensate neglected aerodynamic effects and the arm dynamics. The performance of the proposed architecture has been experimentally evaluated.

137 citations

Proceedings ArticleDOI
24 Dec 2012
TL;DR: A Cartesian impedance control for UAVs equipped with a robotic arm, which is specified in terms of Cartesian space coordinates, and it is possible to exploit the redundancy of the system so as to perform some useful subtasks.
Abstract: A Cartesian impedance control for UAVs equipped with a robotic arm is presented in this paper. A dynamic relationship between generalized external forces acting on the structure and the system motion, which is specified in terms of Cartesian space coordinates, is provided. Through a suitable choice of such variables and with respect to a given task, thanks to the added degrees of freedom given by the robot arm attached to the UAV, it is possible to exploit the redundancy of the system so as to perform some useful subtasks. The hovering control of a quadrotor, equipped with a 3-DOF robotic arm and subject to contact forces and external disturbances acting on some points of the whole structure, is tested in a simulated case study.

136 citations

Journal ArticleDOI
TL;DR: This method, referred to as parallel visual grasp, may represent a valid candidate for applications where online grasp planning is required and a number of experiments are presented, showing the effectiveness of the proposed approach.
Abstract: A method for fast visual grasping of unknown objects with a multifingered robotic hand is presented in this paper. The algorithm is composed of an object surface reconstruction algorithm and a local grasp planner, evolving in parallel. The reconstruction algorithm makes use of images taken by a camera carried by the robot arm. A virtual elastic reconstruction surface is placed around the object. The surface shrinks toward the object until some points intercept the object visual hull. Then, attractive forces with respect to the border of the visual hull are generated so as to compensate for the elastic forces: when an equilibrium between those forces is reached, the surface takes the form of the object shape. Running in parallel to the reconstruction algorithm, the grasp planner moves the fingertips on the current available reconstruction surface, toward points which are optimal (in a local sense) with respect to a number of indices weighting both the grasp quality and the kinematics configuration of the hand. This method, referred to as parallel visual grasp, may represent a valid candidate for applications where online grasp planning is required. A number of experiments are presented, showing the effectiveness of the proposed approach.

108 citations


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Book ChapterDOI
01 Jan 2004
TL;DR: To study the operational behaviour of λ-terms, this work will use the denotational (mathematical) approach to choose a space of semantics values, or denotations, where terms are to be interpreted.
Abstract: To study the operational behaviour of λ-terms, we will use the denotational (mathematical) approach. A denotational semantics for a language is based on the choice of a space of semantics values, or denotations, where terms are to be interpreted. Choosing a space with nice mathematical properties can help in proving the semantic properties of terms, since to this aim standard mathematical techniques can be used.

880 citations

Journal ArticleDOI
TL;DR: A review of the work on data-driven grasp synthesis and the methodologies for sampling and ranking candidate grasps and an overview of the different methodologies are provided, which draw a parallel to the classical approaches that rely on analytic formulations.
Abstract: We review the work on data-driven grasp synthesis and the methodologies for sampling and ranking candidate grasps. We divide the approaches into three groups based on whether they synthesize grasps for known, familiar, or unknown objects. This structure allows us to identify common object representations and perceptual processes that facilitate the employed data-driven grasp synthesis technique. In the case of known objects, we concentrate on the approaches that are based on object recognition and pose estimation. In the case of familiar objects, the techniques use some form of a similarity matching to a set of previously encountered objects. Finally, for the approaches dealing with unknown objects, the core part is the extraction of specific features that are indicative of good grasps. Our survey provides an overview of the different methodologies and discusses open problems in the area of robot grasping. We also draw a parallel to the classical approaches that rely on analytic formulations.

859 citations

01 Jan 2016
TL;DR: L2 gain and passivity techniques in nonlinear control is downloaded for free to help people who are facing with some harmful virus inside their desktop computer.
Abstract: Thank you very much for downloading l2 gain and passivity techniques in nonlinear control. Maybe you have knowledge that, people have search numerous times for their chosen books like this l2 gain and passivity techniques in nonlinear control, but end up in malicious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they are facing with some harmful virus inside their desktop computer.

655 citations

Journal ArticleDOI
TL;DR: The resulting taxonomy incorporates all grasps found in the reviewed taxonomies that complied with the grasp definition and is shown that due to the nature of the classification, the 33 grasp types might be reduced to a set of 17 more generalgrasps if only the hand configuration is considered without the object shape/size.
Abstract: In this paper, we analyze and compare existing human grasp taxonomies and synthesize them into a single new taxonomy (dubbed “The GRASP Taxonomy” after the GRASP project funded by the European Commission). We consider only static and stable grasps performed by one hand. The goal is to extract the largest set of different grasps that were referenced in the literature and arrange them in a systematic way. The taxonomy provides a common terminology to define human hand configurations and is important in many domains such as human–computer interaction and tangible user interfaces where an understanding of the human is basis for a proper interface. Overall, 33 different grasp types are found and arranged into the GRASP taxonomy. Within the taxonomy, grasps are arranged according to 1) opposition type, 2) the virtual finger assignments, 3) type in terms of power, precision, or intermediate grasp, and 4) the position of the thumb. The resulting taxonomy incorporates all grasps found in the reviewed taxonomies that complied with the grasp definition. We also show that due to the nature of the classification, the 33 grasp types might be reduced to a set of 17 more general grasps if only the hand configuration is considered without the object shape/size.

636 citations