Human-Robot Interaction and Collaboration

Permanent URI for this collectionhttps://hdl.handle.net/10125/112407

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A Framework for Advancing Autonomy in Space Robotics: Towards Self-Sustaining Exploration
(2026-01-06) Sanfilippo, Filippo; Esterwood, Connor; You, Sangseok; Venckunas, Tomas; Robert, Lionel
As humanity embarks on deeper space exploration, the integration of robotic autonomy presents transformative potential. % for overcoming challenges associated with exploration, habitat construction, and resource extraction. This paper explores the dynamics of Human-Robot Interaction (HRI), focusing on how autonomous robotic systems engage with unstructured and extreme environments. We examine the role of robotic autonomy, where intelligent decision-making enables exploration, habitat construction, and resource extraction, drawing parallels between human-led and robot-driven space missions. In doing so we systematically investigate the potential for autonomous systems to operate independently in high-risk environments. Using the Autonomy Levels for Unmanned Systems (ALFUS) framework, we assess planetary robots' autonomy in terms of mission complexity (MC), environmental complexity (EC), and external system independence (ESI). Additionally, the Autonomy and Technology Readiness Assessment (ATRA) method supports gradual capability enhancement, providing a roadmap to higher autonomy. Based on this established methodology, we introduce the Autonomous Robotics for Planetary Exploration (ARPE), a novel conceptual framework defining the roles of robotic agents involved, to connect theoretical insights with real-world applications. This work highlights the significance of autonomous decision-making in planetary exploration to enhance mission success and proposes directions for future research on long-term robotic sustainability in extreme environments.
Employees’ Sensemaking Processes in Service Robot Deployment and Use
(2026-01-06) Turunen, Emmi; Tuunainen, Virpi; Liu, Yong
The automation of tasks through AI-enabled technologies is of considerable practical and theoretical significance. Research into service robot-driven automation exposes a variety of interpretations from employees both within and across different workplaces. Understanding by users is crucial yet complex for the successful deployment and interaction with such technologies. In our study, we apply Weick’s enactment theory to examine how employees make sense of a service robot in their work environment. By analyzing 22 interviews, we constructed a process model illustrating how ambiguity triggers the sensemaking process before and during deployment, elucidating how cues are enacted and consolidated into shared understandings that are retained for future application. Our findings provide valuable insights for practitioners by underscoring how the anticipated operational benefits of task automation with service robots intersect with social dynamics and uncertainties. We contribute to the literature on IS and human-robot interaction by revealing how employees perceive service robots in everyday settings.
Shadow Work and Social Inequality in the Age of Domestic Robots: A Q Methodology Approach
(2026-01-06) Kim, Juhee; Kang, Juyoung
This study explores how domestic humanoid robots reconstruct unpaid labor in the form of digital shadow work and influence perceptions of social inequality. Drawing on Illich’s concept of shadow work and Lee’s typology of digital shadow work, we used Q methodology with 30 participants who sorted 40 statements across four types: chore, make-up, routine, and quest. Analysis identified four user perspectives—Realist, Cautious Critic, Pragmatist, and Optimistic Explorer—each reflecting distinct labor burdens and attitudes toward automation. The findings reveal that humanoid robots do not merely reduce domestic tasks but reshape them, often redistributing invisible labor unequally. These dynamics raise concerns about digital inequality and challenge simplistic narratives of convenience. The study highlights the need for inclusive design and policy frameworks to address emerging forms of unpaid labor in human–robot collaboration.
Introduction to the Minitrack on Human-Robot Interaction and Collaboration
(2026-01-06) Esterwood, Connor; Robert, Lionel; Sanfilippo, Filippo; You, Sangseok
Enhancing or Inhibiting? A Literature Analysis of Social Robots and Implications on Well-being Outcomes among Older Adults
(2026-01-06) Xin, Liu; Lyu, Jueni; Cheung, Christy
Social robots have been swiftly adopted among the aging population to boost social interactions and reshape lifestyle patterns. Based on a literature review of 76 research articles, we found that the direct impact of social robots on older adults’ well-being, including psychological, physical, social, and eudaimonic dimensions, can be positive, negative, or non-significant. Contextual factors, including robotic characteristics, geriatric factors, and situational contexts, primarily drive these heterogeneous effects. Based on our findings, we present a comprehensive framework guided by successful aging theory to discuss the future research agenda. Our work helps promote evidence-based social robot design in practice, and we call for closer interdisciplinary collaborations to explore both design factors and behavioral consequences among older adults in advancing the elderly’s well-being and successful aging.
Initial Validation of the Teleoperator-Avatar Robot Interaction Scale (TARX)
(2026-01-06) Banks, Jaime; Harper, Rio; Bowman, Nick
Extant work on human-machine relations indicates humans experience variably social relations with machines. However, there is yet no systematic framework for considering the potential sociality of relations between teleoperators and controlled robots, in addition to their functional associations. We bridge that gap by initially validating a proposed-but-untested measurement model of teleoperator/avatar-robot interaction (the TARX scale) inspired by game-based player-avatar relations. In a lab-based study of human operators’ subjective experiences in remote-controlling a robotic arm, we find support for the hypothesized factor structure comprising four dimensions: Relational closeness, anthropomorphic autonomy, critical concern, and sense of control. Results demonstrate the coherence of socioemotional dimensions of operator experience in addition to cognitive and performance considerations.

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