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The human brain's plasticity allows for the integration of artificial body parts into the human body. Leveraging this, embodied systems realize intuitive interactions with the environment. We introduce a novel concept: embodied swarm robots. Swarm robots constitute a collective of robots working in harmony to achieve a common objective, in our case, serving as functional body parts. Embodied swarm robots can dynamically alter their shape, density, and the correspondences between body parts and individual robots. We contribute an investigation of the influence on embodiment of swarm robot-specific factors derived from these characteristics, focusing on a hand. Our paper is the first to examine these factors through virtual reality (VR) and real-world robot studies to provide essential design considerations and applications of embodied swarm robots. Through quantitative and qualitative analysis, we identified a system configuration to achieve the embodiment of swarm robots.
What will people experience when drones become common in home environments? How will their functions and distances impact human experiences? To explore the potential usage of indoor drones, we conducted a mixed-methods study (N=60) on the reported perceptions of a small flying robot. We employed a factorial experimental design, involving four intended drone functions (\textit{camera}, \textit{education}, \textit{pet}, \textit{unknown}) at two distances (\textit{near}, \textit{far}). Our findings suggest that intended functions significantly influence participants’ perceptions. Among the functions examined, participants found the \textit{camera} useful but annoying, and the \textit{pet} useless but pleasant. The \textit{education} emerged as the most favored function, while the \textit{unknown} function was the least preferred one. Based on these findings, we discuss implications for designing positive interactions between humans and indoor drones, considering aspects such as context, transparency, privacy, technical factors, and personalization.
Applications of drones in emergency response, like firefighting, have been promoted in the past decade. As the autonomy of drones continues to improve, the ways in which they are integrated into firefighting teams and their impact on crews are changing. This demands more understanding of how firefighters perceive and interact with autonomous drones. This paper presents a drone-based system for emergency operations with which firefighters can interact through sound, lights, and a graphical user interface. We use interviews with stakeholders collected in two field trials to explore their perceptions of the interaction and collaboration with drones. Our result shows that firefighters perceived visual interaction as adequate. However, for audio instructions and interfaces, information overload emerges as an essential problem. The potential impact of drones on current work configurations may involve shifting the position of humans closer to supervisory decision-makers and changing the training structure and content.
Small Unmanned Aerial Systems (sUAS) must meet rigorous safety standards when deployed in high-stress emergency response scenarios; however many reported accidents have involved humans in the loop. In this paper, we, therefore, present the HiFuzz testing framework, which uses fuzz testing to identify system vulnerabilities associated with human interactions. HiFuzz includes three distinct levels that progress from a low-cost, limited-fidelity, large-scale, no-hazard environment, using fully simulated Proxy Human Agents, via an intermediate level, where proxy humans are replaced with real humans, to a high-stakes, high-cost, real-world environment. Through applying HiFuzz to an autonomous multi-sUAS system-under-test, we show that each test level serves a unique purpose in revealing vulnerabilities and making the system more robust with respect to human mistakes. While HiFuzz is designed for testing sUAS systems, we further discuss its potential for use in other Cyber-Physical Systems.
As drones become interwoven in human activities, increasingly taking on tasks interpreted as creative and performative, such as choreographed light shows, there is emerging interest in understanding how drones and humans can perform together. Humans have different habits when performing with partners as opposed to solo. How do people adapt their behaviors and perspectives when improvising with robotic partners? To explore these questions, we conducted a study investigating dancer-drone interactions using a system of micro aerial vehicles designed to facilitate improvised solo and partnered dances. Through solo and tandem dances with one or two robots, we analyzed the performers' perceived workflow from semi-structured interviews and quantified their movement patterns during the improvisation. We found that the dancers perceived drone movements through spatial metaphors like the ceiling and gravity, anthropomorphizing drones as props on a stage through position and generated sound. The dancers felt a greater connection in single-drone scenarios and showed heightened avoidance behavior in two-drone situations. Our work shows how a robotic system can energize human dancers to improvise individually and in pairs.