Robots are expected to enter the everyday lives of people to entertain, educate, or support them. It is therefore important that people can intuitively understand the behavior of robots. Oftentimes, the behavior of people is used as a model because of its familiarity. However, it is as yet unclear what the best approach is to design interaction behaviors for non-humanoid robots. In this article, we explore two different approaches toward designing behavior for a service robot. The first concerns the commonly used approach of copying human behavior as closely as possible to the robot ( human-translated ). The second approach was inspired by product design methods. The design of the robot's behavior was optimized for the robot's interaction capabilities and hardware modalities ( robot-optimized ). To evaluate people's responses to the two behavior sets for a tour guide robot, an online video study ( N = 204) and a two-day in-the-wild study ( N > 600) were performed. Results showed that participants responded slightly more positive to robot-optimized behavior and paid attention to robot-optimized behavior for longer. However, participants remembered more details when the robot showed human-translated behavior. Together, the studies show that it is sometimes better for non-humanoid robots to have robot-optimized behaviors rather than human-translated behaviors.

Gestures are important non-verbal signals in human communication. Research with virtual agents and robots has started to add to the scientific knowledge about gestures but many questions with respect to the use of gestures in human-computer interaction are still open. This paper investigates the influence of robot gestures on the users' perceived workload and task performance (i.e. information recall) in a direction-giving task. We conducted a 2 x 2 (robot gestures vs. no robot gestures x easy vs. difficult task) experiment. The results indicate that robot gestures increased user performance and decreased perceived workload in the difficult task but not in the easy task. Thus, robot gestures are a promising means to improve human-robot interaction particularly in challenging tasks.

This video details the development of an intelligent outdoor Guide robot. The main objective is to deploy an innovative robotic guide which is not only able to show information, but to react to the affective states of the users, and to offer location-based services using augmented reality. The scientific challenges concern autonomous outdoor navigation and localization, robust 24/7 operation, affective interaction with visitors through outdoor human and facial feature detection as well as engaging interactive behaviors in an ongoing non-verbal dialogue with the user.

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.

We evaluated the effects of robot gaze behavior on interactions with multiple users in a museum-like setting. We posit that a robot needs to divide its attention between multiple users and may be able to use its gaze to ‘point’ at objects of interest. A 2 (person-oriented [only looking at participants] vs. object-oriented [also looking at artworks] gaze) × 2 (‘favored’ [looked at more] vs. ‘not favored’ [looked at less] by the robot) mixed factorial design (N=57) study was carried out in a museum-like lab setting where a robot talked about two artworks to groups of three participants. Results indicate that ‘favored’ participants did indeed pay more attention to the robot and the artworks. However, surprisingly they paid more attention when the robot did not look over to the object of interest compared to when it did give this gaze cue. The findings suggest that using an object-oriented gaze as a cue for people to look at an object may not carry across readily from person-to-person to human-robot communication. People had trouble interpreting the cue and were possibly distracted by the robot's movement.

How a robot approaches a person greatly determines the interaction that follows. This is particularly relevant when the person has never interacted with the robot before. In human communication, we exchange a multitude of multimodal signals to communicate our intent while we approach others. However, most robots do not have the capabilities to produce such signals and easily communicate their intent. In this paper we propose to communicate intent when a robot approaches a person through functional noise and approach speed. Both were manipulated in a between-subjects experiment (N=40) either slowly increasing at the start of the approach and slowly decreasing when the robot reached the human or maximized at the start and abruptly stopped at the end of the approach. We analyzed questionnaires and video data from the interaction and found that particularly functional noise that in-/decreased in volume was helpful to communicate the robot's intent but only in congruence with an in-/decreasing velocity.

FROG (Fun Robotic Outdoor Guide) is a project that aims to develop an outdoor robotic guide that enriches the visitor experience in touristic sites. This paper is a first step toward a guide robot and presents a case study on how to analyze the visitors' experience and examine opportunities for a future robot guide in the sites. We adopted the participatory design method for mapping the visitor experience; the end users of the tourist sites participated actively in finding and discussing their experience of visiting. Results indicated that visitors especially like the structure of the tour and the stories provided, especially interesting little known facts the guide gives. However, they do not like the rushed pace of a guided tour. When exploring the site by themselves, they enjoy the freedom, the time to make pictures and to concentrate on what interests them. Visitors do not like a lack or overload of information or problems with route finding. Not all guide-related factors that influence a visitor's experience positively can be copied one-on-one to a robot guide. And care needs to be taken to identify those aspects of guided tours and guide behaviors that will be effective for robot-guided tours. In this paper we describe the first step towards the realization of an outdoor robotic guide. We evaluate people's experiences of guided tours to inform the design of robot-guided tours. This analysis forms the basis for ongoing research into the development of effective robot behaviors.