Search results for "Robotic"

Methods for Experimentally Determining Stiffness of a Multi-Axis Machining Centre

2019

This paper deals with global methods for experimentally determining the static stiffness of multi-axis machining centres. Different devices used for measuring deflection, in specific, are explored, where accuracy and usability are highlighted. The methods were tested on a 3-axis CNC milling machine, 2-axis trunnion table and a 6-DOF industrial robot.

Fine Alignment of Thermographic Images for Robotic Inspection of Parts with Complex Geometries

2022

Increasing the efficiency of the quality control phase in industrial production lines through automation is a rapidly growing trend. In non-destructive testing, active thermography techniques are known for their suitability to allow rapid non-contact and full-field inspections. The robotic manipulation of the thermographic instrumentation enables the possibility of performing inspections of large components with complex geometries by collecting multiple thermographic images from optimal positions. The robotisation of the thermographic inspection is highly desirable to improve assessment speed and repeatability without compromising inspection accuracy. Although integrating a robotic setup fo…

A Cognitive Framework for Learning by Imitation

2005

Representation, Recognition and Generation of Actions in the Context of Imitation Learning

2006

The paper deals with the development of a cognitive architecture for learning by imitation in which a rich conceptual representation of the observed actions is built. We adopt the paradigm of conceptual spaces, in which static and dynamic entities are employed to efficiently organize perceptual data, to recognize positional relations, to learn movements from human demonstration and to generate complex actions by combining and sequencing simpler ones. The aim is to have a robotic system able to effectively learn by imitation and which has the capabilities of deeply understanding the perceived actions to be imitated. Experimentation has been performed on a robotic system composed of a PUMA 20…

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…

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…

The human-computer connection: An overview of brain-computer interfaces

2018

This article introduces the field of brain-computer interfaces (BCI), which allows the control of devices without the generation of any active motor output but directly from the decoding of the user’s brain signals. Here we review the current state of the art in the BCI field, discussing the main components of such an interface and illustrating ongoing research questions and prototypes for controlling a large variety of devices, from virtual keyboards for communication to robotics systems to replace lost motor functions and even clinical interventions for motor rehabilitation after a stroke. The article concludes with some insights into the future of BCI.

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, …