Aerial robots are becoming more commonplace within society, but there is limited research about how people interact with these robots in common social situations. In this work, we seek to understand 1) people's natural perceptions and responses to aerial robot flight paths, 2) how people expect to interact with an aerial robot in assorted contexts, and 3) how that work can be scaled up to a multi-human approach. The first two components are prior work where we have conducted both virtual surveys and in-person design sessions with participants. For the next phase, we hope to combine the work exploring the flight paths and situational context, to then expand it from one robot-one human interaction to a multi-human interaction.

The purpose of this project is to understand how people would expect to interact with an Unmanned Aerial Vehicle (UAV) in a social indoor environment under friendly, neutral, or adversarial contexts. The three environments will include one setting with the UAV serving as a tour guide, one as a security guard, and one as a food delivery mechanism. This work is novel in its inquiry into the affective nature of the interaction, comparison across situational contexts, and ability to compare preferences both within and between participants.Our findings will help researchers plan for appropriate safety and comfort measures, while being cognizant of the participants' preferences for and understanding of how drones operate. This study examines realistic indoor scenarios for which each participant designs their preferred interaction and presents exploratory results, including comparison to prior work with respect to motion gestures and comfortable approach distances. Initial findings suggest the importance of visibility of approaches, selecting approach heights relative to the person and based on the context of interaction, and criticality of the initial direction of motion when classifying the communicative content of UAV flight paths.

This body of work presents an iterative process of refinement to understand naive perception of communication using the motion of an unmanned aerial vehicle (UAV). This includes what people believe the UAV is trying to communicate, and how they expect to respond through physical action or emotional response. Previous work in this area sought to communicate without clear definitions of the states attempting to be conveyed. In an attempt to present more concrete states and better understand specific motion perception, this work goes through multiple iterations of state elicitation and label assignment. The lessons learned in this work will be applicable broadly to those interested in defining flight paths, and within the human-robot interaction community as a whole, as it provides a base for those seeking to communicate using non-anthropomorphic robots. We found that the Negative Attitudes towards Robots Scale (NARS) can be an indicator of how a person is likely to react to a UAV, the emotional content they are likely to perceive from a message being conveyed, and it is an indicator for the personality characteristics they are likely to project upon the UAV. We also see that people commonly associate motions from other non-verbal communication situations onto UAVs. Flight specific recommendations are to use a dynamic retreating motion from a person to encourage following, use a perpendicular motion to their field of view for blocking, simple descending motion for landing, and to use either no motion or large altitude changes to encourage watching. Overall, this research explores the communication from the UAV to the bystander through its motion, to see how people respond physically and emotionally. Advisor: Brittany A. Duncan

This project seeks to generate small Unmanned Aerial System (sUAS) flight paths that are broadly understood by the general population and can communicate states about both the sUAS and its understanding of the world. Previous work in sUAS flight paths has sought to communicate intent, destination, or emotion of the system without focusing on concrete states (e.g., low battery, landing, etc.). This work leverages biologically-based flight paths and experimental methodologies from human-human and human-humanoid robot interactions to assess the understanding of avian flight paths to communicate sUAS states to novice users. If successful, this work should inform: the human-robot interaction community about the perception of flight paths, sUAS manufacturers on how their systems could communicate with both operators and bystanders, and end users on ways to communicate with others when flying systems in public spaces. General design implications and future directions of work are suggested to build on the results here, which suggest that novice users gravitate towards labels they understand (draw attention and landing) while avoiding more technical labels (lost sensor).

This paper presents an investigation of human comfort with a small Unmanned Aerial Vehicle (sUAV) through a study offering a comparison of comfort with a sUAV versus a ground vehicle. Current research on human comfort with sUAVs has been limited to a single previous study, which did not include free flight, and while ground vehicle distancing has been studied, it has never been directly compared to a sUAV. The novelty in the approach is the use of a motion capture room to achieve smooth trajectories and precise measurements, while conducting the first free flight study to compare human comfort after interaction with aerial versus ground vehicles (within subjects, N=16). These results will contribute to understanding of social, collaborative, and assistive robots, with implications for general human-robot interactions as they evolve to include aerial vehicles. Based on the reduced stress and distance (36.5cm or 1.2ft) for ground vehicles and increased stress and distance (65.5cm or 2.15ft) for sUAVs, it is recommended that studies be conducted to understand the implications of design features on comfort in interactions with sUAVs and how they differ from those with ground robots.