Exploring the Interaction Space to Support Running Experiences with Drones

Drones show great potential to support sports activities such as running, cycling, and rowing. Yet, little is known about the way athletesperceive and experience the presence of a drone in their sporting context, also in relation to the placement of drones around them.Earlier works in designing human-drone-interactions (HDI) provide design tactics to develop drones tailored to runners. However, thespaces where a drone can be placed to interact with the runner is likely to be different from what is found in more commonly studiedstatic scenarios of drone proxemics. We present a study that explores the positions of a drone around a runner, and their perception ofit, in an outdoor running setting. We positioned the drone at thirty locations around them and conducted a quantitative study ofperceived safety with the drone and comfort in tracking the drone as well as facets of usability of a drone in this scenario such asaudibility of the speaker, loudness of the drone noise, and preferred angle of image capture. Our results indicate that runners preferdrones to be placed in their field of view and within a horizontal distance of 8–12m, and prefer angles of images capture that show theirposture along the frontal and sagittal planes. This study is unique in the way it investigates user experience and drone positioning in anaturalistic setting. It builds upon existing work in which some of these aspects were investigated under lab conditions. With ourapproach, we were also able to generate a segmented interaction space that researchers could utilize to make informed decisions whenpositioning drones for studies in a running contex

Drone Communication with Naive Humans

In recent times, drones have become ubiquitous and are tackling problems in such diverse areas as construction, disease control and product delivery. With the rise of drone usage in areas frequented by humans, natural human-drone interaction has become an important phenomenon to study. Designing behaviors for effective drone communication with humans is complex but necessary, especially if drones are to operate in human environments.We present research on drone communication with naive humans, that is, with people interacting with drones who are not themselves participating in whatever task with which the drone is engaged. Drones need to be able to communicate warnings and requests for assistance from humans that they just happen to encounter, and we are attempting to establish design methodologies for creating behaviors that can be interpreted by such naive humans.We have performed a user study (N=21) and presented the results. The results suggest that our approach works and most of the participants can recognize a drone's intentions from its demonstrations

Applications of Affective Computing in Human-Robot Interaction: state-of-art and challenges for manufacturing

The introduction of collaborative robots aims to make production more flexible, promoting a greater interaction between humans and robots also from physical point of view. However, working closely with a robot may lead to the creation of stressful situations for the operator, which can negatively affect task performance. In Human-Robot Interaction (HRI), robots are expected to be socially intelligent, i.e., capable of understanding and reacting accordingly to human social and affective clues. This ability can be exploited implementing affective computing, which concerns the development of systems able to recognize, interpret, process, and simulate human affects. Social intelligence is essential for robots to establish a natural interaction with people in several contexts, including the manufacturing sector with the emergence of Industry 5.0. In order to take full advantage of the human-robot collaboration, the robotic system should be able to perceive the psycho-emotional and mental state of the operator through different sensing modalities (e.g., facial expressions, body language, voice, or physiological signals) and to adapt its behaviour accordingly. The development of socially intelligent collaborative robots in the manufacturing sector can lead to a symbiotic human-robot collaboration, arising several research challenges that still need to be addressed. The goals of this paper are the following: (i) providing an overview of affective computing implementation in HRI; (ii) analyzing the state-of-art on this topic in different application contexts (e.g., healthcare, service applications, and manufacturing); (iii) highlighting research challenges for the manufacturing sector

Comfortable Approach Distance with small Unmanned Aerial Vehicles

This paper presents the first known human-subject study of comfortable approach distance and height for human interaction with a small unmanned aerial vehicle (sUAV), finding no conclusive difference in comfort with a sUAV approaching a human at above head height or below head height. Understanding the amount, if any, of discomfort introduced by a sUAV flying in close proximity to a human is critical for law enforcement, crowd control, entertainment, or flying personal assistants. Previous work has focused on how humans interact with each other or with unmanned ground vehicles, and the experimental methods typically rely on the human participant to consciously express distress. The approach taken was to duplicate the experimental set up in human proxemics studies, while adding psychophysiological sensing, under the hypothesis that human-robot interaction will mirror human-human interaction. The 16 participant, within-subjects experiment did not confirm this hypothesis. Instead a sUAV above height of a “tall” person in human experiments (2.13 m) did not produce statistically different heart rate variability nor cause the participant to stop the robot further away than for a sUAV at a “short” height (1.52 m). The lack of effect may be due to two possible confounds: i) duplicating prior human proxemics experiments did not capture how a sUAV would likely move or interact and ii) telling the participants that the robot could not hurt them. Despite possible confounding, the results raise the question of whether human-human psychological and physical distancing behavior transfers to human-aerial robot interactions

Modeling Human-Robot Interaction in Three Dimensions

This dissertation answers the question: Can a small autonomous UAV change a person's movements by emulating animal behaviors? Human-robot interaction (HRI) has generally been limited to engagements with ground robots at human height or shorter, essentially working on the same two dimensional plane, but this ignores potential interactions where the robot may be above the human such as small un- manned aerial vehicles (sUAVs) for crowd control and evacuation or for underwater or space vehicles acting as assistants for divers or astronauts. The dissertation combines two approaches {behavioral robotics and HRI {to create a model of \Comfortable Distance" containing the information about human-human and human-ground robot interactions and extends it to three dimensions. Behavioral robotics guides the ex- amination and transfer of relevant behaviors from animals, most notably mammals, birds, and ying insects, into a computational model that can be programmed in simulation and on a sUAV. The validated model of proxemics in three dimensions makes a fundamental contribution to human-robot interaction. The results also have significant benefit to the public safety community, leading to more effective evacuation and crowd control, and possibly saving lives. Three findings from this experiment were important in regards to sUAVs for evacuation: i) expressions focusing on the person, rather than the area, are good for decreasing time (by 7.5 seconds, p <.0001) and preference (by 17.4 %, p <.0001), ii) personal defense behaviors are best for decreasing time of interaction (by about 4 seconds, p <.004), while site defense behaviors are best for increasing distance of interaction (by about .5 m, p <.003), and iii) Hediger's animal zones may be more applicable than Hall's human social zones when considering interactions with animal behaviors in sUAVs

McNair Scholars Research Journal Volume XV

https://commons.stmarytx.edu/msrj/1014/thumbnail.jp

McNair Scholars Research Journal Volume XV

https://commons.stmarytx.edu/msrj/1014/thumbnail.jp