Shared Perspectives for Unforeseen Response in Human-Robot Teams (SPUR)

Project begins 2025.

Integrating robots into collaborative environments, particularly in domains requiring adaptability and problem-solving, has become increasingly prevalent. This technological shift has brought to the forefront the critical importance of shared mental models (SMMs) in human-robot teams (HRTs). SMMs represent the overlapping mental models between team members of tasks, roles, and team members’ capabilities, which are fundamental to successful teamwork, especially in high-stakes settings like space exploration or disaster response. While extensively studied in human teams, the unique characteristics of human-robot teaming introduce novel complexities to SMM development and maintenance

This project aims to investigate the comprehensive cycle of SMM adaptation in human-robot teams, encompassing initial formation, adaptation to novel challenges, and integration of new knowledge for future applications. The research focuses on immediate adaptive responses and long-term learning processes involving SMM that enhance team performance in dynamic, uncertain environments.

This proposal addresses the following research questions, assuming a team of human and robotic agents with an initial SMM including a goal and a nominal task sequence/plan, which is disrupted by an unexpected event:

• How can the HRT SMM evolve and be updated as novel tasks are completed? How can the multi-agent HRTs accomplish their goals through creative problem-solving?
• How can human-robot teams recognize the limitations of their existing SMM when confronted with novel, unexpected situations? Investigate the current understanding of each member’s capabilities, identifying gaps in knowledge about how they can assist each other.
• What factors influence human-robot teams’ ability to engage in creative problem-solving and adaptively evolve their SMMs in response to these challenges?
• To enhance future performance, what strategies can human-robot teams employ to incorporate these adapted models and newly acquired knowledge into their operations? How can human-robot interaction design be optimized to facilitate development and adaptation in novel contexts?

Previous projects by project team include:

• Estimating and Calibrating Situation Awareness for Improving Human-Robot Teaming Performance
• Enhancing UGV Navigation with Adaptive Human Intervention

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