Astrid Weiss

Hobbit, a care robot supporting independent living at home

One option to address the challenge of demographic transition is to build robots that enable aging in place. Falling has been identified as the most relevant factor to cause a move to a care facility. The Hobbit project combines research from robotics, gerontology, and human-robot interaction to develop a care robot which is capable of fall prevention and detection as well as emergency detection and handling. Moreover, to enable daily interaction with the robot, other functions are added, such as bringing objects, offering reminders, and entertainment. The interaction with the user is based on a multimodal user interface including automatic speech recognition, text-to-speech, gesture recognition, and a graphical touch-based user interface. We performed controlled laboratory user studies with a total of 49 participants (aged 70 plus) in three EU countries (Austria, Greece, and Sweden). The collected user responses on perceived usability, acceptance, and affordability of the robot demonstrate a positive reception of the robot from its target user group. This article describes the principles and system components for navigation and manipulation in domestic environments, the interaction paradigm and its implementation in a multimodal user interface, the core robot tasks, as well as the results from the user studies, which are also reflected in terms of lessons we learned and we believe are useful to fellow researchers. We present a care robot for aging in place by means of fall prevention/detection.Detailed description of sensor set-up, hardware, and the multimodal user interface.Detailed description of major software components and implemented robot tasks.Proof-of-concept user study (49 user) on usability, acceptance, and affordability.

A methodological variation for acceptance evaluation of Human-Robot Interaction in public places

Several variations of methodological approaches are used to study the social acceptance in human-robot interaction. Due to the introduction of robots in the home, working practice and usage typically informing the design of new forms of technology are missing. Studying social acceptance in human-robot interaction thus needs new methodological concepts. We propose a so called breaching experiment with additional ethnographic observation to close this gap. To investigate the methodological concept we have been conducting a field trial on a public place. We gathered feedback using questionnaires, in order to estimate whether this method can be beneficially to evaluate social acceptance. We could show that breaching experiments can be a useful method to investigate social acceptance in the field.

Robots asking for directions: the willingness of passers-by to support robots

This paper reports about a human-robot interaction field trial conducted with the autonomous mobile robot ACE (Autonomous City Explorer) in a public place, where the ACE robot needs the support of human passers-by to find its way to a target location. Since the robot does not possess any prior map knowledge or GPS support, it has to acquire missing information through interaction with humans. The robot thus has to initiate communication by asking for the way, and retrieves information from passers-by showing the way by gestures (pointing) and marking goal positions on a still image on the touch screen of the robot. The aims of the field trial where threefold: (1) Investigating the aptitude of the navigation architecture, (2) Evaluating the intuitiveness of the interaction concept for the passers-by, (3) Assessing peoples willingness to support the ACE robot in its task, i.e. assessing the social acceptability. The field trial demonstrates that the architecture enables successful autonomous path finding without any prior map knowledge just by route directions given by passers-by. An additional street survey and observational data moreover attests the intuitiveness of the interaction paradigm and the high acceptability of the ACE robot in the public place.

“I Love This Dog”—Children’s Emotional Attachment to the Robotic Dog AIBO

In this paper we present a methodological variation of assessing emotional attachment of children and adults to the robotic pet AIBO, using an atypical application area (a shopping mall) and leaving the participation in the study as totally voluntary. This free exploration case study was situated in a shopping mall for three reasons: People do not expect a robotic pet in this context (first time reaction) and the context allows to address a high number of possible participants and to create an awareness for robots in general. To investigate the methodological concept and to find out if such a setting can be beneficial for a better understanding of the influence of first time contact with a robotic pet to the emotional attachment, we conducted the case study on three consecutive work days. We could show that this method reveals interesting and novel aspects on the development of emotional attachment.

Trends in the living room and beyond

Investigating the context home becomes more and more necessary for future developments of interactive TV services and of new interaction techniques. In this paper, findings from two ethnographic studies are presented. In these studies a new methodological variation of cultural probing called creative cultural probing (CCP) was developed. The aim of our research was to investigate activities and interaction techniques in the living room and beyond. In this paper, the results of the studies are presented and some major trends for the home context are highlighted. The studies indicate that supporting social interaction and personal activities as well as personalization, security and communication needs have to be addressed in the future more thoroughly.

Autonomous vs. tele-operated: how people perceive human-robot collaboration with hrp-2

Effective collaboration between robots and humans is not only a question of interface design and usability, but also of user experience and social acceptance. To investigate these aspects for Human-Robot Collaboration with the HRP-2 robot, two video-based focus groups enhanced with “creative stimuli” were conducted. The following research question was addressed: “Is the HRP-2 robot perceived differently in an autonomous collaboration condition compared to a tele-operated collaboration condition, in terms of social acceptance and user experience?” The results show that participants in general are open to a humanoid robot as working partner as long as there is a clear distinction between a human and a robot, in terms of tasks and working procedures. Furthermore, participants stated a positive attitude toward the remotely-controlled HRP-2 robot.

FORE-Watch – the clock that tells you when to use: persuading users to align their energy consumption with green power availability

Besides saving energy, using it at the right time (i.e. when there is a supply surplus, and the power is produced by sustainable power sources such as hydroelectricity or wind) is an important possibility to achieve positive effects for the environment. To enable the user to align their behavior with the dynamics of the energy generation they need to be informed about the current status of power supply and grid capacity. Furthermore, to be able to plan their behavior and possibly delay or advance consumption activities to more proper moments they also need to have access to high-quality forecasts about the future status of green energy supply. In this paper we present an ambient display design solution based on a common watch that is optimized for providing this information in an unobtrusive, ambient and persuasive way. We present and discuss requirements identified by use of literature analysis, focus groups and end-user questionnaires, outline approaches to calculate basic power generation forecasts based on weather forecast data and present an ambient interface concept designed to meet the identified requirements. We conclude that the developed approach has high potential to support desired behavior changes, and that achieving acceptable accuracy levels for the generation forecast is feasible with relatively little effort.

Exploring human-robot cooperation possibilities for semiconductor manufacturing

This paper presents notions of a novel human-centered, integrated production system based on the intelligent cooperation between humans, robots and automation systems in the clean room context. In semiconductor manufacturing and in particular for short-term interactions with robotic systems like turn taking (an operator performs some work, hands over a lot box to the robot to perform some work and so on), it is still an open issue how the ideal relationship between the human and the intelligent (autonomous) system should look like. We present two case studies conducted together with Infineon Technologies Austria AG, with the overall aim to explore the interaction scope of operators and the cooperation potential of the robotic systems in the semiconductor manufacturing context.

Don't stand so close to me: users' attitudinal and behavioral responses to personal space invasion by robots

When around humans, one might expect that a social robot would act according to the social norms people expect of each other. When someone does not adhere to a prevalent social norm, people usually feel threatened and uncomfortable. In comparison, insight is needed into what is perceived as socially normative behavior for robots. We conducted an experiment in which a robot approached a participant in order to determine the effect of personal space invasion. We manipulated the agent-type (human/robot) and the approach speed (slow/fast) of the agent towards the participant. Unexpectedly, our results show that the participants displayed more compensatory behavior toward the robot than toward the human confederate. Interestingly, we found that participants tended to trust the faster robot more compared and the faster human less. We consider these responses toward personal space invasion as an indication that people react differently to robots as they do to humans, and with more intensity.

Learning grasps with topographic features

We present a system for grasping unknown objects, even from piles or cluttered scenes, given a point cloud. Our method is based on the topography of a given scene and abstracts grasp-relevant structures to enable machine learning techniques for grasping tasks. We describe how Height Accumulated Features (HAF) and their extension, Symmetry Height Accumulated Features, extract grasp relevant local shapes. We investigate grasp quality using an F-score metric. We demonstrate the gain and the expressive power of HAF by comparing its trained classifier with one that resulted from training on simple height grids. An efficient way to calculate HAF is presented. We describe how the trained grasp classifier is used to explore the whole grasp space and introduce a heuristic to find the most robust grasp. We show how to use our approach to adapt the gripper opening width before grasping. In robotic experiments we demonstrate different aspects of our system on three robot platforms: a Schunk seven-degree-of-freedom arm, a PR2 and a Kuka LWR arm. We perform tasks to grasp single objects, autonomously unload a box and clear the table. Thereby we show that our approach is easily adaptable and robust with respect to different manipulators. As part of the experiments we compare our algorithm with a state-of-the-art method and show significant improvements. Concrete examples are used to illustrate the benefit of our approach compared with established grasp approaches. Finally, we show advantages of the symbiosis between our approach and object recognition.