Search results for " Rob"

Enabling robotic adaptive behaviour capabilities for new industry 4.0 automated quality inspection paradigms

2020

The seamless integration of industrial robotic arms with server computers, sensors and actuators can revolutionise the way in which automated non-destructive testing (NDT) is performed and conceived. Achieving effective integration and realising the full potential of robotic systems presents significant challenges, since robots, sensors and end-effector tools are often not necessarily designed to be put together and form a holistic system. This paper presents recent breakthroughs, opening up new scenarios for the inspection of product quality in advanced manufacturing. Many years of research have brought to software platforms the ability to integrate external data acquisition instrumentatio…

Macroelement Model for the Progressive-Collapse Analysis of Infilled Frames

2021

A new multistrut macromodel for the analysis of the progressive-collapse response of infilled reinforced concrete (RC) frames is presented in this paper. The model consists of three struts: two outer infinitely rigid and resistant struts and one inner fiber-section strut. The inclination of the struts as well as the stress-strain response are modulated by two parameters that are obtained by means of analytical correlations provided in the paper. The latter link the geometric and mechanical properties of an infilled frame to the geometric configuration and mechanical response of the equivalent strut model. This confers the model the capability to adapt to consider different collapse configur…

L’informatica umanistica: attualità e prospettive

2010

Robot acceptance model for care (RAM-care) : A principled approach to the intention to use care robots

2020

Robots are emerging in welfare services, and organizations require information on whether novel technologies are approved among staff. On the basis of technology acceptance theories, this study proposes a model that adds a principled approach to the intention to use care robots. Data of 544 professionals with care robot experience were collected. The use intention was predicted by usefulness, enjoyment, social influence, and attitude. Respondents who found robots useful and accepted by their colleagues were more likely to view robot use as consistent with their personal values. The care robot acceptance model supports consideration of the profession-specific context in robotization. peerRev…

Learning high-level manipulative tasks through imitation

2006

This paper presents ConSCIS, Conceptual Space based Cognitive Imitation System, which tightly links low-level data processing with knowledge representation in the context of robot imitation. Our focus is on the program-level imitation: we are interested in the final effects of actions on objects, and not on the particular kinematic or dynamic properties of the motion. The same architecture is used both to analyze and represent the task to be imitated, and to perform the imitation by generalizing in novel and different circumstances. The implemented experimental scenario is a two dimensional world populated with various objects in which observation/imitation takes place. To validate our appr…

Embodied responses to musical experience detected by human bio-feedback brain features in a geminoid augmented architecture

2018

Abstract This paper presents the conceptual framework for a study of musical experience and the associated architecture centred on Human-Humanoid Interaction (HHI). On the grounds of the theoretical and experimental literature on the biological foundation of music, the grammar of music perception and the perception and feeling of emotions in music hearing, we argue that music cognition is specific and that it is realized by a cognitive capacity for music that consists of conceptual and affective constituents. We discuss the relationship between such constituents that enables understanding, that is extracting meaning from music at the different levels of the organization of sounds that are f…

Modelling the insect Mushroom Bodies: Application to sequence learning

2015

Learning and reproducing temporal sequences is a fundamental ability used by living beings to adapt behaviour repertoire to environmental constraints. This paper is focused on the description of a model based on spiking neurons, able to learn and autonomously generate a sequence of events. The neural architecture is inspired by the insect Mushroom Bodies (MBs) that are a crucial centre for multimodal sensory integration and behaviour modulation. The sequence learning capability coexists, within the insect brain computational model, with all the other features already addressed like attention, expectation, learning classification and others. This is a clear example that a unique neural struc…

Indoor Scene Understanding using Non-Conventional Cameras

2020

Humans understand environments effortlessly, under a wide variety of conditions, by the virtue of visual perception. Computer vision for similar visual understanding is highly desirable, so that machines can perform complex tasks by interacting with the real world, to assist or entertain humans. In this regard, we are particularly interested in indoor environments, where humans spend nearly all their lifetime.This thesis specifically addresses the problems that arise during the quest of the hierarchical visual understanding of indoor scenes.On the side of sensing the wide 3D world, we propose to use non-conventional cameras, namely 360º imaging and 3D sensors. On the side of understanding, …

Robust optimality of linear saturated control in uncertain linear network flows

2008

We propose a novel approach that, given a linear saturated feedback control policy, asks for the objective function that makes robust optimal such a policy. The approach is specialized to a linear network flow system with unknown but bounded demand and politopic bounds on controlled flows. All results are derived via the Hamilton-Jacobi-Isaacs and viscosity theory.

ROBUST CONTROL STRATEGIES FOR MULTI—INVENTORY SYSTEMS WITH AVERAGE FLOW CONSTRAINTS

2006

Abstract In this paper we consider multi—inventory systems in presence of uncertain demand. We assume that i) demand is unknown but bounded in an assigned compact set and ii) the control inputs (controlled flows) are subject to assigned constraints. Given a long—term average demand, we select a nominal flow that feeds such a demand. In this context, we are interested in a control strategy that meets at each time all possible current demands and achieves the nominal flow in the average. We provide necessary and sufficient conditions for such a strategy to exist and we characterize the set of achievable flows. Such conditions are based on linear programming and thus they are constructive. In …