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1. Aerial Flight Paths for Communication: How Participants Perceive and Intend to Respond to Drone Movements

   https://doi.org/10.1145/3434073.3444645  

   Bevins, Alisha ; Duncan, Brittany A. ( March 2021 , Proceedings of the 2021 ACM/IEEE International Conference on Human-Robot Interaction)

   null (Ed.)

   This work has developed an iteratively refined understanding of participants’ natural perceptions and responses to unmanned aerial vehicle (UAV) flight paths, or gestures. This includes both what they believe the UAV is trying to communicate to them, in addition to how they expect to respond through physical action. Previous work in this area has focused on eliciting gestures from participants to communicate specific states, or leveraging gestures that are observed in the world rather than on understanding what the participants believe is being communicated and how they would respond. This work investigates previous gestures either created or categorized by participants to understand the perceived content of their communication or expected response, through categories created by participant free responses and confirmed through forced choice testing. The human-robot interaction community can leverage this work to better understand how people perceive UAV flight paths, inform future designs for non-anthropomorphic robot communications, and apply lessons learned to elicit informative labels from people who may or may not be operating the vehicle. We found that the Negative Attitudes towards Robots Scale (NARS) can be a good indicator of how we can expect a person to react to a robot. Recommendations are also provided to use motion approaching/retreating from a person to encourage following, perpendicular to their field of view for blocking, and to use either no motion or large altitude changes to encourage viewing. 

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2. Investigation of Unmanned Aerial Vehicle Gesture Perceptibility and Impact of Viewpoint Variance

   https://doi.org/10.1109/ICRA48506.2021.9561094  

   Fletcher, Paul ; Luther, Angeline ; Duncan, Brittany ; Detweiler, Carrick ( May 2021 , 2021 IEEE International Conference on Robotics and Automation (ICRA))

   Unmanned Aerial Vehicle (UAV) flight paths have been shown to communicate meaning to human observers, similar to human gestural communication. This paper presents the results of a UAV gesture perception study designed to assess how observer viewpoint perspective may impact how humans perceive the shape of UAV gestural motion. Robot gesture designers have demonstrated that robots can indeed communicate meaning through gesture; however, many of these results are limited to an idealized range of viewer perspectives and do not consider how the perception of a robot gesture may suffer from obfuscation or self-occlusion from some viewpoints. This paper presents the results of three online user-studies that examine participants' ability to accurately perceive the intended shape of two-dimensional UAV gestures from varying viewer perspectives. We used a logistic regression model to characterize participant gesture classification accuracy, demonstrating that viewer perspective does impact how participants perceive the shape of UAV gestures. Our results yielded a viewpoint angle threshold from beyond which participants were able to assess the intended shape of a gesture's motion with 90% accuracy. We also introduce a perceptibility score to capture user confidence, time to decision, and accuracy in labeling and to understand how differences in flight paths impact perception across viewpoints. These findings will enable UAV gesture systems that, with a high degree of confidence, ensure gesture motions can be accurately perceived by human observers. 

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3. Investigation of unmanned aerial vehicle gesture perceptibility and impact of viewpoint variance

   Fletcher, P. ; Detweiler, C. ; Duncan, B. ( May 2021 , IEEE International Conference on Robotics and Automation)

   null (Ed.)

   Unmanned Aerial Vehicle (UAV) flight paths have been shown to communicate meaning to human observers, similar to human gestural communication. This paper presents the results of a UAV gesture perception study designed to assess how observer viewpoint perspective may impact how humans perceive the shape of UAV gestural motion. Robot gesture designers have demonstrated that robots can indeed communicate meaning through gesture; however, many of these results are limited to an idealized range of viewer perspectives and do not consider how the perception of a robot gesture may suffer from obfuscation or self-occlusion from some viewpoints. This paper presents the results of three online user-studies that examine participants’ ability to accurately perceive the intended shape of two-dimensional UAV gestures from varying viewer perspectives. We used a logistic regression model to characterize participant gesture classification accuracy, demonstrating that viewer perspective does impact how participants perceive the shape of UAV gestures. Our results yielded a viewpoint angle threshold from beyond which participants were able to assess the intended shape of a gesture’s motion with 90% accuracy. We also introduce a perceptibility score to capture user confidence, time to decision, and accuracy in labeling and to understand how differences in flight paths impact perception across viewpoints. These findings will enable UAV gesture systems that, with a high degree of confidence, ensure gesture motions can be accurately perceived by human observers. 

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4. An Exploratory Analysis of Air Traffic Controller Speech Intelligibility Using Voice Data from a Simulation Experiment

   https://doi.org/10.1177/1071181322661450  

   Vance Paredes, Yancy ; Cooke, Nancy J. ( September 2022 , Proceedings of the Human Factors and Ergonomics Society Annual Meeting)

   Air Traffic Controllers (ATCs) communicate with pilots through radio communication. Speech intelligibility is vital in ensuring that the message is conveyed accurately. Factors such as speech rate affect this. Additionally, workload and stress have been shown to affect how people communicate significantly. In this paper, we attempt to analyze the voice data of ATCs who participated in a simulated experiment in the context of these non-verbal aspects of communication, particularly transmission length and speech rate. To better understand, we analyzed our data at two levels: aggregate and individual. Moreover, we focused on a single participant to see how such non-verbal characteristics evolve. Understanding these intricacies would contribute to building automated detectors in real-time voice transmissions that would leverage technology to avert any incidents brought about by stress and workload. 

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5. Communication-Aware Robotics: Exploiting Motion for Communication

   https://doi.org/10.1146/annurev-control-071420-080708  

   Muralidharan, Arjun ; Mostofi, Yasamin ( May 2021 , Annual Review of Control, Robotics, and Autonomous Systems)

   In this review, we present a comprehensive perspective on communication-aware robotics, an area that considers realistic communication environments and aims to jointly optimize communication and navigation. The main focus of the article is theoretical characterization and understanding of performance guarantees. We begin by summarizing the best prediction an unmanned vehicle can have of the channel quality at unvisited locations. We then consider the case of a single robot, showing how it can mathematically characterize the statistics of its traveled distance until connectivity and further plan its path to reach a connected location with optimality guarantees, in real channel environments and with minimum energy consumption. We then move to the case of multiple robots, showing how they can utilize their motions to enable robust information flow. We consider two specific robotic network configurations—robotic beamformers and robotic routers—and mathematically characterize properties of the co-optimum motion–communication decisions. 

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