Social Roles and Baseline Proxemic Preferences for a Domestic Service Robot

© The Author(s) 2014. This article is published with open access at Springerlink.com. This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. The work described in this paper was conducted within the EU Integrated Projects LIREC (LIving with Robots and intEractive Companions, funded by the European Commission under contract numbers FP7 215554, and partly funded by the ACCOMPANY project, a part of the European Union’s Seventh Framework Programme (FP7/2007–2013) under grant agreement n287624The goal of our research is to develop socially acceptable behavior for domestic robots in a setting where a user and the robot are sharing the same physical space and interact with each other in close proximity. Specifically, our research focuses on approach distances and directions in the context of a robot handing over an object to a userPeer reviewe

Differences of Human Perceptions of a Robot Moving using Linear or Slow in, Slow out Velocity Profiles When Performing a Cleaning Task

We investigated how a robot moving with different velocity profiles affects a person's perception of it when working together on a task. The two profiles are the standard linear profile and a profile based on the animation principles of slow in, slow out. The investigation was accomplished by running an experiment in a home context where people and the robot cooperated on a clean-up task. We used the Godspeed series of questionnaires to gather people's perception of the robot. Average scores for each series appear not to be different enough to reject the null hypotheses, but looking at the component items provides paths to future areas of research. We also discuss the scenario for the experiment and how it may be used for future research into using animation techniques for moving robots and improving the legibility of a robot's locomotion

Integrating Constrained Experiments in Long-term Human-Robot Interaction using Task– and Scenario–based Prototyping

© 2015 The Author(s). Published with license by Taylor & Francis© Dag Sverre Syrdal, Kerstin Dautenhahn, Kheng Lee Koay, and Wan Ching Ho. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The moral rights of the named author(s) have been asserted. Permission is granted subject to the terms of the License under which the work was published. Please check the License conditions for the work which you wish to reuse. Full and appropriate attribution must be given. This permission does not cover any third party copyrighted material which may appear in the work requested.In order to investigate how the use of robots may impact everyday tasks, 12 participants interacted with a University of Hertfordshire Sunflower robot over a period of 8 weeks in the university’s Robot House.. Participants performed two constrained tasks, one physical and one cognitive , 4 times over this period. Participant responses were recorded using a variety of measures including the System Usability Scale and the NASA Task Load Index . The use of the robot had an impact on the experienced workload of the participants differently for the two tasks, and this effect changed over time. In the physical task, there was evidence of adaptation to the robot’s behaviour. For the cognitive task, the use of the robot was experienced as more frustrating in the later weeks.Peer reviewedFinal Published versio

Nonverbal Communication During Human-Robot Object Handover. Improving Predictability of Humanoid Robots by Gaze and Gestures in Close Interaction

Meyer zu Borgsen S. Nonverbal Communication During Human-Robot Object Handover. Improving Predictability of Humanoid Robots by Gaze and Gestures in Close Interaction. Bielefeld: Universität Bielefeld; 2020.This doctoral thesis investigates the influence of nonverbal communication on human-robot object handover. Handing objects to one another is an everyday activity where two individuals cooperatively interact. Such close interactions incorporate a lot of nonverbal communication in order to create alignment in space and time. Understanding and transferring communication cues to robots becomes more and more important as e.g. service robots are expected to closely interact with humans in the near future. Their tasks often include delivering and taking objects. Thus, handover scenarios play an important role in human-robot interaction. A lot of work in this field of research focuses on speed, accuracy, and predictability of the robot’s movement during object handover. Still, robots need to be enabled to closely interact with naive users and not only experts. In this work I present how nonverbal communication can be implemented in robots to facilitate smooth handovers. I conducted a study on people with different levels of experience exchanging objects with a humanoid robot. It became clear that especially users with only little experience in regard to interaction with robots rely heavily on the communication cues they are used to on the basis of former interactions with humans. I added different gestures with the second arm, not directly involved in the transfer, to analyze the influence on synchronization, predictability, and human acceptance. Handing an object has a special movement trajectory itself which has not only the purpose of bringing the object or hand to the position of exchange but also of socially signalizing the intention to exchange an object. Another common type of nonverbal communication is gaze. It allows guessing the focus of attention of an interaction partner and thus helps to predict the next action. In order to evaluate handover interaction performance between human and robot, I applied the developed concepts to the humanoid robot Meka M1. By adding the humanoid robot head named Floka Head to the system, I created the Floka humanoid, to implement gaze strategies that aim to increase predictability and user comfort. This thesis contributes to the field of human-robot object handover by presenting study outcomes and concepts along with an implementation of improved software modules resulting in a fully functional object handing humanoid robot from perception and prediction capabilities to behaviors enhanced and improved by features of nonverbal communication

Aerial social force model: a new framework to accompany people using autonomous flying robots

© 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.We proposed a novel Aerial Social Force Model (ASFM) that allows autonomous flying robots to accompany humans in urban environments in a safe and comfortable manner. To date, we are not aware of other state-of-the-art method that accomplish this task. The proposed approach is a 3D version of the Social Force Model (SFM) for the field of aerial robots which includes an interactive human-robot navigation scheme capable of predicting human motions and intentions so as to safely accompany them to their final destination. ASFM also introduces a new metric to fine-tune the parameters of the force model, and to evaluate the performance of the aerial robot companion based on comfort and distance between the robot and humans. The presented approach is extensively validated in diverse simulations and real experiments, and compared against other similar works in the literature. ASFM attains remarkable results and shows that it is a valuable framework for social robotics applications, such as guiding people or human-robot interaction.Peer ReviewedPostprint (author's final draft

Views from within a narrative : Evaluating long-term human-robot interaction in a naturalistic environment using open-ended scenarios

Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. Date of acceptance: 16/06/2014This article describes the prototyping of human–robot interactions in the University of Hertfordshire (UH) Robot House. Twelve participants took part in a long-term study in which they interacted with robots in the UH Robot House once a week for a period of 10 weeks. A prototyping method using the narrative framing technique allowed participants to engage with the robots in episodic interactions that were framed using narrative to convey the impression of a continuous long-term interaction. The goal was to examine how participants responded to the scenarios and the robots as well as specific robot behaviours, such as agent migration and expressive behaviours. Evaluation of the robots and the scenarios were elicited using several measures, including the standardised System Usability Scale, an ad hoc Scenario Acceptance Scale, as well as single-item Likert scales, open-ended questionnaire items and a debriefing interview. Results suggest that participants felt that the use of this prototyping technique allowed them insight into the use of the robot, and that they accepted the use of the robot within the scenarioPeer reviewe

Robot companion: a social-force based approach with human awareness-navigation in crowded environments

Robots accompanying humans is one of the core capacities every service robot deployed in urban settings should have. We present a novel robot companion approach based on the so-called Social Force Model (SFM). A new model of robot-person interaction is obtained using the SFM which is suited for our robots Tibi and Dabo. Additionally, we propose an interactive scheme for robot’s human-awareness navigation using the SFM and prediction information. Moreover, we present a new metric to evaluate the robot companion performance based on vital spaces and comfortableness criteria. Also, a multimodal human feedback is proposed to enhance the behavior of the system. The validation of the model is accomplished throughout an extensive set of simulations and real-life experiments.Peer ReviewedPostprint (author’s final draft

What could assistance robots learn from assistance dogs?

These studies are part of our broader project that aims at revealing relevant aspects of human-dog interactions, which could help to develop and test robot social behaviour. We suggest that the cooperation between assistance dogs and their disabled owners could serve as a model to design successful assistance robot–human interactions. In Study 1, we analysed the behaviour of 32 assistance dog–owner dyads performing a fetch and carry task. In addition to important typical behaviours (attracting attention, eye-contact, comprehending pointing gestures), we found differences depending on how experienced the dyad was and whether the owner used a wheel chair or not. In Study 2 we investigated the reactions of a subsample of dogs to unforeseen difficulties during a retrieving task. We revealed different types of communicative and displacement behaviours, and importantly, dogs showed a strong commitment to execute the insoluble task or at least their behaviours lent a “busy” appearance to them, which can attenuate the owners’ disappointment. We suggest that assistant robots should communicate their inability to solve a problem using simple behaviours (non-verbal vocalisation, orientation alternation), and/or could show displacement behaviours rather than simply not performing the task. In sum, we propose that assistant dogs’ communicative behaviours and problem solving strategies could inspire the development of the relevant functions and social behaviours of assistance robots