Manja Lohse

SPENCER: A Socially Aware Service Robot for Passenger Guidance and Help in Busy Airports

We present an ample description of a socially compliant mobile robotic platform, which is developed in the EU-funded project SPENCER. The purpose of this robot is to assist, inform and guide passengers in large and busy airports. One particular aim is to bring travellers of connecting flights conveniently and efficiently from their arrival gate to the passport control. The uniqueness of the project stems from the strong demand of service robots for this application with a large potential impact for the aviation industry on one side, and on the other side from the scientific advancements in social robotics, brought forward and achieved in SPENCER. The main contributions of SPENCER are novel methods to perceive, learn, and model human social behavior and to use this knowledge to plan appropriate actions in real-time for mobile platforms. In this paper, we describe how the project advances the fields of detection and tracking of individuals and groups, recognition of human social relations and activities, normative human behavior learning, socially-aware task and motion planning, learning socially annotated maps, and conducting empirical experiments to assess socio-psychological effects of normative robot behaviors.

BEHAVE-II: The Revised Set of Measures to Assess Users’ Attitudinal and Behavioral Responses to a Social Robot

In order to inform the design of behaviors for robots that share domestic and public spaces with people, it is important to know what robot behavior is considered as normative. The work reported in this paper stems from the premise that what is perceived as socially normative behavior for people may differ from what is considered socially normative for a robot. This paper details the development of a data collection instrument, BEHAVE-II, for assessing user responses toward a robot’s behavior using both attitudinal and behavioral responses. To test the validity and reliability of the BEHAVE-II instrument, a human-robot interaction experiment was conducted in which a robot or a human invaded the personal space of a participant. We found that participants’ reactions were stronger when their personal space was invaded by a robot compared with a person. This points to the fact that humans are actually highly sensible whether robots’ adhere to social norms which underlines the importance of the BEHAVE-II instrument.

Evaluating extrovert and introvert behaviour of a domestic robot — a video study

Human-robot interaction (HRI) research is here presented into social robots that have to be able to interact with inexperienced users. In the design of these robots many research findings of human-human interaction and human-computer interaction are adopted but the direct applicability of these theories is limited because a robot is different from both humans and computers. Therefore, new methods have to be developed in HRI in order to build robots that are suitable for inexperienced users. In this paper we present a video study we conducted employing our robot BIRON (Bielefeld robot companion) which is designed for use in domestic environments. Subjects watched the system during the interaction with a human and rated two different robot behaviours (extrovert and introvert). The behaviours differed regarding verbal output and person following of the robot. Aiming to improve human-robot interaction, participantspsila ratings of the behaviours were evaluated and compared.

Classes of Applications for Social Robots: A User Study

The paper introduces an online user study on applications for social robots with 127 participants. The potential users proposed 570 application scenarios based on the appearance and functionality of four robots presented (AIBO, BARTHOC, BIRON, iCat). The items were grouped into 13 categories which are interpreted and discussed by means of four dimensions: public vs. private use, intensity of interaction, complexity of interaction model, and functional vs. human-like appearance. The interpretation lead to three classes of applications for social robots according to the degree of social interaction: (1) Specialized Applications where the robot has to perform clearly defined tasks which are delegated by a user, (2) Public Applications which are directed to the communication with many users, and (3) Individual Applications with the need of a highly elaborated social model to maintain a variety of situations with few people.

Systemic interaction analysis (SInA) in HRI

Recent developments in robotics enable advanced human-robot interaction. Especially interactions of novice users with robots are often unpredictable and, therefore, demand for novel methods for the analysis of the interaction in systemic ways. We propose Systemic Interaction Analysis (SInA) as a method to jointly analyze system level and interaction level in an integrated manner using one tool. The approach allows us to trace back patterns that deviate from prototypical interaction sequences to the distinct system components of our autonomous robot. In this paper, we exemplarily apply the method to the analysis of the follow behavior of our domestic robot BIRON. The analysis is the basis to achieve our goal of improving human-robot interaction iteratively.

The Effect of a Robot's Social Character on Children Task Engagement: Peer Versus Tutor

An increasing number of applications for social robots focuses on learning and playing with children. One of the unanswered questions is what kind of social character a robot should have in order to positively engage children in a task. In this paper, we present a study on the effect of two different social characters of a robot (peer vs. tutor) on children’s task engagement. We derived peer and tutor robot behaviors from the literature and we evaluated the two robot characters in a WoZ study where 10 pairs of children aged 6 to 9 played Tangram puzzles with a Nao robot. Our results show that in the peer character condition, children paid attention to the robot and the task for a longer period of time and solved the puzzles quicker and better than in the tutor character condition.

Robot etiquette: how to approach a pair of people?

Research has been carried out on robots approaching one person [1, 3, 4]. However, further research is needed on robots approaching groups of people. In the study reported in this paper, we studied participants who were paired up for a task and assessed their perception and behaviors as they were approached by a robot from various angles. On an individual level, participants liked the frontal approaches, and they disliked being approached from the back. However, we found that the presence of a task-partner influenced participants’ comfort with a robot approaching (i.e. when the robot approaches and one is standing behind the task-partner). Apart from the positioning of the individuals, the layout of the room, position of furniture and doors, also seemed to influence their experience. This pilot study was performed with a limited number of participants (N=30). However, the study offers preliminary insights into the factors that influence the choice for a robot approach direction when approaching a pair of people that are focused on a task. Categories and Subject DescriptorsH1.2 [Information Systems]: User/Machine systems – Human factorsGeneral TermsHuman Factors, Experimentation

Robots to motivate elderly people: Present and future challenges

In this paper we argue for the development of new methodological approaches to create and evaluate robots for elderly-care, which offer support for the psychological determinants of the quality of life of elderly people. Relevant determinants, such as mood, self-efficacy and happiness are discussed in this paper in relation to older people. We offer an overview of previous work on robots offering psychological support and analyse the various methodological challenges in studying the effects of motivational and psycho-therapeutic robots on elderly peoples psychological well-being.

Dynamics of social positioning patterns in group-robot interactions

When a mobile robot interacts with a group of people, it has to consider its position and orientation. We introduce a novel study aimed at generating hypotheses on suitable behavior for such social positioning, explicitly focusing on interaction with small groups of users and allowing for the temporal and social dynamics inherent in most interactions. In particular, the interactions we look at are approach, converse and retreat. In this study, groups of three participants and a telepresence robot (controlled remotely by a fourth participant) solved a task together while we collected quantitative and qualitative data, including tracking of positioning/orientation and ratings of the behaviors used. In the data we observed a variety of patterns that can be extrapolated to hypotheses using inductive reasoning. One such pattern/hypothesis is that a (telepresence) robot could pass through a group when retreating, without this affecting how comfortable that retreat is for the group members. Another is that a group will rate the position/orientation of a (telepresence) robot as more comfortable when it is aimed more at the center of that group.

A modeling framework for user-driven iterative design of autonomous systems

Many researchers in human-robot interaction have acknowledged the fact that iterative design is necessary to optimize the robots for the interaction with the users. However, few iterative user studies have been reported. We believe that one reason for this is that setting up systems for iterative studies is cumbersome because the system architectures do not support iterative design. In the paper, we address this problem by interlinking usability research with system development. In a first user study, we identify requirements and concepts for a new framework that eases the employment of autonomous robots in the iterative design process. With a second user study we show how robot behaviors are implemented in the new framework and how it enables the developer to efficiently make changes to these behaviors.