Users' attitudes toward service robots in South Korea

Park, Eunil,Pobil, Angel P. del Emerald Group Publishing Limited 2013 The Industrial robot Vol.40 No.1

<B>Purpose</B> - The purpose of this paper is to understand users' acceptance of service robots by integrating perceived enjoyment of service robots and users' need to belong in a technology acceptance model (TAM) framework. Service robots are currently being used in homes and firms to provide various services. <B>Design/methodology/approach</B> - The authors conducted a web-based survey from 904 users in South Korea to test a research model and employed structural equation modelling as the analysis method. <B>Findings</B> - This study found that perceived enjoyment and the need to belong played an important role in the perceived ease of use and usefulness of service robots. Furthermore, it was discovered that the research supported relationships proposed by the original TAM with regard to users' attitudes and intentions to use service robots. Therefore, this study provides a framework to understand users' acceptance of service robots. <B>Originality/value</B> - This paper is of value to researchers designing and improving service robots for use in our society.

A Pilot Study on Saccadic Adaptation Experiments with Robots

Chinellato, E.,Antontelli, M.,del Pobil, A.P. SPRINGER-VERLAG 2012 Lecture Notes in Computer Science Vol.7375 No.-

Is a furry robot more animal-like?

Zhao manping,P. del Pobil 한국HCI학회 2013 한국HCI학회 학술대회 Vol.2013 No.1

Pet robots (or robotic pets) are being considered as social actors or social companions and used in lots of areas, such as educational fields or robot-assisted therapy(RAA). By the development of the pet robots, the features of pet robots have become more and more comfortable and animal-like for users; however, there are many limits in this developing progress. How can we design pet robots look more real? How can we make pet robots more perfect to use? How can we make pet robots more interactive with users? We are always looking forward to making the human-robot relationship more natural . These highly discussed problems should be solved as soon as possible to satisfy the rising demand of pet robots. In this paper, we focused on the surface of pet robots. Surface of the pet robots is an important factor and by comparing two different surface types, we can know the difference using different qualities for each type.

Predicting the internal model of a robotic system from its morphology

Duran, Angel J.,del Pobil, Angel P. Elsevier 2018 Robotics and autonomous systems Vol.110 No.-

<P><B>Abstract</B></P> <P>The estimation of the internal model of a robotic system results from the interaction of its morphology, sensors and actuators, with a particular environment. Model learning techniques, based on supervised machine learning, are widespread for determining the internal model. An important limitation of such approaches is that once a model has been learnt, it does not behave properly when the robot morphology is changed. From this it follows that there must exist a relationship between them. We propose a model for this correlation between the morphology and the internal model parameters, so that a new internal model can be predicted when the morphological parameters are modified. Different neural network architectures are proposed to address this high dimensional regression problem. A case study is analyzed in detail to illustrate and evaluate the performance of the approach, namely, a pan–tilt robot head executing saccadic movements. The best results are obtained for an architecture with parallel neural networks. Our results can be instrumental in state-of-the-art trends such as self-reconfigurable robots, reproducible research, cyber–physical robotic systems or cloud robotics, in which internal models would available as shared knowledge, so that robots with different morphologies can readily exhibit a particular behavior in a given environment.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A model to correlate the morphology and internal model parameters for a robotic system is presented. </LI> <LI> Different neural network architectures are proposed to solve this regression problem. </LI> <LI> A case study is used to illustrate and evaluate the neural network proposed. </LI> <LI> Due to the properties of the maximum likelihood estimator, the best performance is reached with parallel neural network architectures. </LI> </UL> </P>

An Active System for Visually-Guided Reaching in 3D across Binocular Fixations

Martinez-Martin, Ester,del Pobil, Angel P.,Chessa, Manuela,Solari, Fabio,Sabatini, Silvio P. Hindawi Publishing Corporation 2014 The Scientific World Journal Vol.2014 No.-

<P>Based on the importance of relative disparity between objects for accurate hand-eye coordination, this paper presents a biological approach inspired by the cortical neural architecture. So, the motor information is coded in egocentric coordinates obtained from the allocentric representation of the space (in terms of disparity) generated from the egocentric representation of the visual information (image coordinates). In that way, the different aspects of the visuomotor coordination are integrated: an active vision system, composed of two vergent cameras; a module for the 2D binocular disparity estimation based on a local estimation of phase differences performed through a bank of Gabor filters; and a robotic actuator to perform the corresponding tasks (visually-guided reaching). The approach's performance is evaluated through experiments on both simulated and real data.</P>

A Biologically Inspired Approach for Robot Depth Estimation

Martinez-Martin, Ester,del Pobil, Angel P. Hindawi 2018 Computational intelligence and neuroscience Vol.2018 No.-

<P>Aimed at building autonomous service robots, reasoning, perception, and action should be properly integrated. In this paper, the depth cue has been analysed as an early stage given its importance for robotic tasks. So, from neuroscience findings, a hierarchical four-level <I>dorsal</I> architecture has been designed and implemented. Mainly, from a stereo image pair, a set of complex Gabor filters is applied for estimating an egocentric quantitative disparity map. This map leads to a quantitative depth scene representation that provides the raw input for a qualitative approach. So, the reasoning method infers the data required to make the right decision at any time. As it will be shown, the experimental results highlight the robust performance of the biologically inspired approach presented in this paper.</P>

Implicit Sensorimotor Mapping of the Peripersonal Space by Gazing and Reaching

Chinellato, E,Antonelli, M,Grzyb, B J,del Pobil, A P IEEE 2011 IEEE transactions on autonomous mental development Vol.3 No.1

<P>Primates often perform coordinated eye and arm movements, contextually fixating and reaching towards nearby objects. This combination of looking and reaching to the same target is used by infants to establish an implicit visuomotor representation of the peripersonal space, useful for both oculomotor and arm motor control. In this work, taking inspiration from such behavior and from primate visuomotor mechanisms, a shared sensorimotor map of the environment, built on a radial basis function framework, is configured and trained by the coordinated control of eye and arm movements. Computational results confirm that the approach seems especially suitable for the problem at hand, and for its implementation on a real humanoid robot. By exploratory gazing and reaching actions, either free or goal-based, the artificial agent learns to perform direct and inverse transformations between stereo vision, oculomotor, and joint-space representations. The integrated sensorimotor map that allows to contextually represent the peripersonal space through different vision and motor parameters is never made explicit, but rather emerges thanks to the interaction of the agent with the environment.</P>

Facial Recognition Patterns of Children and Adults Looking at Robotic Faces

Park, Eunil,Kim, Ki Joon,del Pobil, Angel P. SAGE Publications 2012 International Journal of Advanced Robotic Systems Vol.9 No.1

Pose Estimation Through Cue Integration: A Neuroscience-Inspired Approach

Chinellato, E.,Grzyb, B. J.,del Pobil, A. P. IEEE 2012 IEEE Transactions on Cybernetics Vol.42 No.2

<P>The aim of this paper is to improve the skills of robotic systems in their interaction with nearby objects. The basic idea is to enhance visual estimation of objects in the world through the merging of different visual estimators of the same stimuli. A neuroscience-inspired model of stereoptic and perspective orientation estimators, merged according to different criteria, is implemented on a robotic setup and tested in different conditions. Experimental results suggest that the integration of multiple monocular and binocular cues can make robot sensory systems more reliable and versatile. The same results, compared with simulations and data from human studies, show that the model is able to reproduce some well-recognized neuropsychological effects.</P>

The Effects of Multimodal Feedback and Gender on Task Performance of Stylus Pen Users

Park, Eunil,Kim, Ki Joon,del Pobil, Angel P. SAGE Publications 2012 International Journal of Advanced Robotic Systems Vol.9 No.1