Multi-modal Open World User Identification

User identification is an essential step in creating a personalised long-term interaction with robots. This requires learning the users continuously and incrementally, possibly starting from a state without any known user. In this article, we describe a multi-modal incremental Bayesian network with online learning, which is the first method that can be applied in such scenarios. Face recognition is used as the primary biometric, and it is combined with ancillary information, such as gender, age, height, and time of interaction to improve the recognition. The Multi-modal Long-term User Recognition Dataset is generated to simulate various human-robot interaction (HRI) scenarios and evaluate our approach in comparison to face recognition, soft biometrics, and a state-of-the-art open world recognition method (Extreme Value Machine). The results show that the proposed methods significantly outperform the baselines, with an increase in the identification rate up to 47.9% in open-set and closed-set scenarios, and a significant decrease in long-term recognition performance loss. The proposed models generalise well to new users, provide stability, improve over time, and decrease the bias of face recognition. The models were applied in HRI studies for user recognition, personalised rehabilitation, and customer-oriented service, which showed that they are suitable for long-term HRI in the real world

Pepper4Museum: Towards a Human-like Museum Guide

With the recent advances in technology, new ways to engage visitors in a museum have been proposed. Relevant examples range from the simple use of mobile apps and interactive displays to virtual and augmented reality settings. Recently social robots have been used as a solution to engage visitors in museum tours, due to their ability to interact with humans naturally and familiarly. In this paper, we present our preliminary work on the use of a social robot, Pepper in this case, as an innovative approach to engaging people during museum visiting tours. To this aim, we endowed Pepper with a vision module that allows it to perceive the visitor and the artwork he is looking at, as well as estimating his age and gender. These data are used to provide the visitor with recommendations about artworks the user might like to see during the visit. We tested the proposed approach in our research lab and preliminary experiments show its feasibility

Personal Guides: Heterogeneous Robots Sharing Personal Tours in Multi-Floor Environments

GidaBot is an application designed to setup and run a heterogeneous team of robots to act as tour guides in multi-floor buildings. Although the tours can go through several floors, the robots can only service a single floor, and thus, a guiding task may require collaboration among several robots. The designed system makes use of a robust inter-robot communication strategy to share goals and paths during the guiding tasks. Such tours work as personal services carried out by one or more robots. In this paper, a face re-identification/verification module based on state-of-the-art techniques is developed, evaluated offline, and integrated into GidaBot’s real daily activities, to avoid new visitors interfering with those attended. It is a complex problem because, as users are casual visitors, no long-term information is stored, and consequently, faces are unknown in the training step. Initially, re-identification and verification are evaluated offline considering different face detectors and computing distances in a face embedding representation. To fulfil the goal online, several face detectors are fused in parallel to avoid face alignment bias produced by face detectors under certain circumstances, and the decision is made based on a minimum distance criterion. This fused approach outperforms any individual method and highly improves the real system’s reliability, as the tests carried out using real robots at the Faculty of Informatics in San Sebastian show.This work has been partially funded by the Basque Government, Spain, grant number IT900-16, and the Spanish Ministry of Economy and Competitiveness (MINECO), grant number RTI2018-093337-B-I00

AveroBot: An audio-visual dataset for people re-identification and verification in human-robot interaction

Intelligent technologies have pervaded our daily life, making it easier for people to complete their activities. One emerging application is involving the use of robots for assisting people in various tasks (e.g., visiting a museum). In this context, it is crucial to enable robots to correctly identify people. Existing robots often use facial information to establish the identity of a person of interest. But, the face alone may not offer enough relevant information due to variations in pose, illumination, resolution and recording distance. Other biometric modalities like the voice can improve the recognition performance in these conditions. However, the existing datasets in robotic scenarios usually do not include the audio cue and tend to suffer from one or more limitations: most of them are acquired under controlled conditions, limited in number of identities or samples per user, collected by the same recording device, and/or not freely available. In this paper, we propose AveRobot, an audio-visual dataset of 111 participants vocalizing short sentences under robot assistance scenarios. The collection took place into a three-floor building through eight different cameras with built-in microphones. The performance for face and voice re-identification and verification was evaluated on this dataset with deep learning baselines, and compared against audio-visual datasets from diverse scenarios. The results showed that AveRobot is a challenging dataset for people re-identification and verification

Smart Rollators Aid Devices: Current Trends and Challenges.

Mobility loss has a major impact on autonomy. Smart rollators have been proposed to enhance human abilities when conventional devices are not enough. Many human-robot interaction systems have been proposed in the last decade in this area. Comparative analysis shows that mechanical issues aside, they mainly differ in first, equipped sensors and actuators; second, input interface; third, operation modes, and fourth adaptation capabilities. This article presents a review and a tentative taxonomy of approaches during the last 6 years. In total, 92 papers have been reviewed. We have discarded works not focused on humanrobot interaction or focused only on mechanical adaptation. A critical analysis is provided after the review and classification, highlighting systems tested with their target population.This work was supported by the the Spanish project RTI2018-096701-B-C21 and the Swedish Knowledge Foun dation (KKS) through the research profile Embedded Sensor Systems for Health Plus (ESS−H+) at Malardalen University, ¨ Sweden

Brave new world: service robots in the frontline

Purpose – The service sector is at an inflection point with regard to productivity gains and service industrialization similar to the industrial revolution in manufacturing that started in the eighteenth century. Robotics in combination with rapidly improving technologies like artificial intelligence (AI), mobile, cloud, big data and biometrics will bring opportunities for a wide range of innovations that have the potential to dramatically change service industries. The purpose of this paper is to explore the potential role service robots will play in the future and to advance a research agenda for service researchers. Design/methodology/approach – This paper uses a conceptual approach that is rooted in the service, robotics and AI literature. Findings – The contribution of this paper is threefold. First, it provides a definition of service robots, describes their key attributes, contrasts their features and capabilities with those of frontline employees, and provides an understanding for which types of service tasks robots will dominate and where humans will dominate. Second, this paper examines consumer perceptions, beliefs and behaviors as related to service robots, and advances the service robot acceptance model. Third, it provides an overview of the ethical questions surrounding robot-delivered services at the individual, market and societal level. Practical implications – This paper helps service organizations and their management, service robot innovators, programmers and developers, and policymakers better understand the implications of a ubiquitous deployment of service robots. Originality/value – This is the first conceptual paper that systematically examines key dimensions of robot-delivered frontline service and explores how these will differ in the future

Impact of Iris Size and Eyelids Coupling on the Estimation of the Gaze Direction of a Robotic Talking Head by Human Viewers

International audiencePrimates - and in particular humans-are very sensitive to the eye direction of congeners. Estimation of gaze of others is one of the basic skills for estimating goals, intentions and desires of social agents, whether they are humans or avatars. When building robots, one should not only supply them with gaze trackers but also check for the readability of their own gaze by human partners. We conducted experiments that demonstrate the strong impact of the iris size and the position of the eyelids of an iCub humanoid robot on gaze reading performance by human observers. We comment on the importance of assessing the robot's ability of displaying its intentions via clearly legible and readable gestures

Selected Computing Research Papers Volume 7 June 2018

Contents Critical Evaluation of Arabic Sentimental Analysis and Their Accuracy on Microblogs (Maha Al-Sakran) Evaluating Current Research on Psychometric Factors Affecting Teachers in ICT Integration (Daniel Otieno Aoko) A Critical Analysis of Current Measures for Preventing Use of Fraudulent Resources in Cloud Computing (Grant Bulman) An Analytical Assessment of Modern Human Robot Interaction Systems (Dominic Button) Critical Evaluation of Current Power Management Methods Used in Mobile Devices (One Lekula) A Critical Evaluation of Current Face Recognition Systems Research Aimed at Improving Accuracy for Class Attendance (Gladys B. Mogotsi) Usability of E-commerce Website Based on Perceived Homepage Visual Aesthetics (Mercy Ochiel) An Overview Investigation of Reducing the Impact of DDOS Attacks on Cloud Computing within Organisations (Jabed Rahman) Critical Analysis of Online Verification Techniques in Internet Banking Transactions (Fredrick Tshane