ORIGINAL RESEARCH article
Front. Robot. AI
Sec. Human-Robot Interaction
This article is part of the Research TopicSocial Robot Navigation – Opportunities, Algorithms, Tools, and SystemsView all 3 articles
From Complexity to Commercial Readiness: Industry Insights on Bridging Gaps in Human-Robot Interaction and Social Robot Navigation
Provisionally accepted
- Rutgers, The State University of New Jersey, New Brunswick, United States
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This paper examines the evolving landscape of mobile robotics, focusing on challenges faced by roboticists working in industry when integrating robots into human-populated environments. Through interviews with sixteen industry professionals specializing in social mobile robotics, we examined two primary research questions: 1) What approaches to person detection and representation are used in industry? And 2) How does the relationship between industry and academia impact the research process? Our findings reveal diverse approaches to human detection, ranging from basic obstacle avoidance to advanced systems that differentiate among classes of humans. We suggest that robotic system design overall and human detection in particular are influenced by whether researchers use a framework of safety or sociality, how they approach building complex systems, and how they develop metrics for success. Additionally, we highlight the gaps and synergies between industry and academic research, particularly regarding commercial readiness and the incorporation of human-robot interaction (HRI) principles into robotic development. This study underscores the importance of addressing the complexities of social navigation in real-world settings and suggests that strengthening avenues of communication between industry and academia will help to shape a sustainable role for robots in the physical and social world.
Keywords: mobile robots, navigation, Industry, interview, qualitative research, Person detection
Received: 23 Sep 2025; Accepted: 28 Nov 2025.
Copyright: © 2025 Moe and Greenberg. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Benjamin Greenberg
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