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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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Analyzing the Fluency of Human-Robot Interactions
Fluency---described as the ``coordinated meshing of joint activities between members of a well-synchronized team''---is essential to human-robot team success. Human teams achieve fluency through rich, often mostly implicit, communication. A key challenge in bridging the gap between industry and academia is understanding what influences human perception of a fluent team experience to better optimize human-robot fluency in industrial environments. This paper addresses this challenge by developing an online experiment featuring videos that vary the timing of human and robot actions to influence perceived team fluency. Our results support three broad conclusions. First, we did not see differences across most subjective fluency measures. Second, people report interactions as more fluent as teammates stay more active. Third, reducing delays when humans' tasks depend on robots increases perceived team fluency.
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- Award ID(s):
- 1651822
- PAR ID:
- 10404887
- Date Published:
- Journal Name:
- AAAI 2023 Spring Symposium on HRI in Academia and Industry: Bridging the Gap
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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