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The human-robot interaction (HRI) field has rec- ognized the importance of enabling robots to interact with teams. Human teams rely on effective communication for suc- cessful collaboration in time-sensitive environments. Robots can play a role in enhancing team coordination through real-time assistance. Despite significant progress in human-robot teaming research, there remains an essential gap in how robots can effectively communicate with action teams using multimodal interaction cues in time-sensitive environments. This study addresses this knowledge gap in an experimental in-lab study to investigate how multimodal robot communication in action teams affects workload and human perception of robots. We explore team collaboration in a medical training scenario where a robotic crash cart (RCC) provides verbal and non-verbal cues to help users remember to perform iterative tasks and search for supplies. Our findings show that verbal cues for object search tasks and visual cues for task reminders reduce team workload and increase perceived ease of use and perceived usefulness more effectively than a robot with no feedback. Our work contributes to multimodal interaction research in the HRI field, highlighting the need for more human-robot teaming research to understand best practices for integrating collaborative robots in time-sensitive environments such as in hospitals, search and rescue, and manufacturing applications.
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Fluent Coordination in Proximate Human Robot Teaming
Fluent coordination is important in order for teams to work well together. In proximate teaming scenarios, fluent teams tend to perform more successfully. Recent work suggests robots can support fluency in human-robot teams a number of ways, including using nonverbal cues and anticipating human intention. However, this area of research is still in its early stages. We identify some of the key challenges in this research space, specifically individual variations during teaming, knowledge and task transfer, co-training prior to task execution, and long-term interactions. We then discuss possible paths forward, including leveraging human adaptability, to promote more fluent teaming.
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- Award ID(s):
- 1734482
- PAR ID:
- 10145650
- Date Published:
- Journal Name:
- In Proceedings of the Robotics, Science, and Systems (RSS) Workshop on AI and Its Alternatives for Shared Autonomy in Assistive and Collaborative Robotics
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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