Experimental evaluation of a multi-modal user interface for a robotic service

This paper reports the experimental evaluation of a Multi- Modal User Interface (MMUI) designed to enhance the user experience in terms of service usability and to increase acceptability of assistive robot systems by elderly users. The MMUI system offers users two main modalities to send commands: they are a GUI, usually running on the tablet attached to the robot, and a SUI, with a wearable microphone on the user. The study involved fifteen participants, aged between 70 and 89 years old, who were invited to interact with a robotic platform customized for providing every-day care and services to the elderly. The experimental task for the participants was to order a meal from three different menus using any interaction modality they liked. Quantitative and qualitative data analyses demonstrate a positive evaluation by users and show that the multi-modal means of interaction can help to make elderly-robot interaction more flexible and natural

The multi-modal interface of Robot-Era multi-robot services tailored for the elderly

Socially assistive robotic platforms are now a realistic option for the long-term care of ageing populations. Elderly users may benefit from many services provided by robots operating in different environments, such as providing assistance inside apartments, serving in shared facilities of buildings or guiding people outdoors. In this paper, we present the experience gained within the EU FP7 ROBOT-ERA project towards the objective of implementing easy-to-use and acceptable service robotic system for the elderly. In particular, we detail the user-centred design and the experimental evaluation in realistic environments of a web-based multi-modal user interface tailored for elderly users of near future multi-robot services. Experimental results demonstrate positive evaluation of usability and willingness to use by elderly users, especially those less experienced with technological devices who could benefit more from the adoption of robotic services. Further analyses showed how multi-modal modes of interaction support more flexible and natural elderly–robot interaction, make clear the benefits for the users and, therefore, increase its acceptability. Finally, we provide insights and lessons learned from the extensive experimentation, which, to the best of our knowledge, is one of the largest experimentation of a multi-robot multi-service system so far

Talking About Task Progress: Towards Integrating Task Planning and Dialog for Assistive Robotic Services

The use of service robots to assist ageing people in their own homes has the potential to allow people to maintain their independence, increasing their health and quality of life. In many assistive applications, robots perform tasks on people’s behalf that they are unable or unwilling to monitor directly. It is important that users be given useful and appropriate information about task progress. People being assisted in homes and other realworld environments are likely be engaged in other activities while they wait for a service, so information should also be presented in an appropriate, nonintrusive manner. This paper presents a human-robot interaction experiment investigatingwhat type of feedback people prefer in verbal updates by a service robot about distributed assistive services. People found feedback about time until task completion more useful than feedback about events in task progress or no feedback. We also discuss future research directions that involve giving non-expert users more input into the task planning process when delays or failures occur that necessitate replanning or modifying goals

A real-time human-robot interaction system based on gestures for assistive scenarios

Natural and intuitive human interaction with robotic systems is a key point to develop robots assisting people in an easy and effective way. In this paper, a Human Robot Interaction (HRI) system able to recognize gestures usually employed in human non-verbal communication is introduced, and an in-depth study of its usability is performed. The system deals with dynamic gestures such as waving or nodding which are recognized using a Dynamic Time Warping approach based on gesture specific features computed from depth maps. A static gesture consisting in pointing at an object is also recognized. The pointed location is then estimated in order to detect candidate objects the user may refer to. When the pointed object is unclear for the robot, a disambiguation procedure by means of either a verbal or gestural dialogue is performed. This skill would lead to the robot picking an object in behalf of the user, which could present difficulties to do it by itself. The overall system — which is composed by a NAO and Wifibot robots, a KinectTM v2 sensor and two laptops — is firstly evaluated in a structured lab setup. Then, a broad set of user tests has been completed, which allows to assess correct performance in terms of recognition rates, easiness of use and response times.Postprint (author's final draft

Social robots for older users: a possibility to support assessment and social interventions

In the last decades, various researches in the field of robotics have created numerous opportunities for innovative support of the older population. The goal of this work was to review and highlight how social robots can help the daily life of older people, and be useful also as assessment tools. We will underline the aspects of usability and acceptability of robotic supports in the psychosocial work with older persons. The actual usability of the system influences the perception of the ease of use only when the user has no or low experience, while expert users’ perception is related to their attitude towards the robot. This finding should be more deeply analysed because it may have a strong influence on the design of future interfaces for elderly-robot interaction. Robots can play an important role to tackle the societal challenge of the growing older population. The authors report some recent studies with older users, where it was demonstrated that the acceptability of robotics during daily life activities, and also in cognitive evaluation, could be supported by social robot

Methodology and themes of human-robot interaction: a growing research field

Original article can be found at: http://www.intechweb.org/journal.php?id=3 Distributed under the Creative Commons Attribution License. Users are free to read, print, download and use the content or part of it so long as the original author(s) and source are correctly credited.This article discusses challenges of Human-Robot Interaction, which is a highly inter- and multidisciplinary area. Themes that are important in current research in this lively and growing field are identified and selected work relevant to these themes is discussed.Peer reviewe

Adaptive modality selection algorithm in robot-assisted cognitive training

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Interaction of socially assistive robots with users is based on social cues coming from different interaction modalities, such as speech or gestures. However, using all modalities at all times may be inefficient as it can overload the user with redundant information and increase the task completion time. Additionally, users may favor certain modalities over the other as a result of their disability or personal preference. In this paper, we propose an Adaptive Modality Selection (AMS) algorithm that chooses modalities depending on the state of the user and the environment, as well as user preferences. The variables that describe the environment and the user state are defined as resources, and we posit that modalities are successful if certain resources possess specific values during their use. Besides the resources, the proposed algorithm takes into account user preferences which it learns while interacting with users. We tested our algorithm in simulations, and we implemented it on a robotic system that provides cognitive training, specifically Sequential memory exercises. Experimental results show that it is possible to use only a subset of available modalities without compromising the interaction. Moreover, we see a trend for users to perform better when interacting with a system with implemented AMS algorithm.Peer ReviewedPostprint (author's final draft