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Help or Hindrance: Understanding the Impact of Robot Communication in Action Teams

Tauhid Tanjim, Jonathan St. George, Kevin Ching, Angelique Taylor

TL;DR

The paper investigates how multimodal robot communication affects team workload and perception in time-sensitive action-team contexts using a robotic crash cart in medical simulations. It employs a Wizard-of-Oz RCC delivering speech and light cues across three conditions, measuring outcomes with NASA-TLX and TAM. Findings show that verbal object-search cues combined with visual reminders (C2) improve perceived usefulness and ease of use while reducing workload compared with unimodal or no feedback, underscoring the value of task- and space-aware communication. The work highlights the role of spatial dynamics and embodiment in HRI design and offers practical guidance for deploying collaborative robots in hospitals, search-and-rescue, and manufacturing, along with directions for adaptive multimodal strategies.

Abstract

The human-robot interaction (HRI) field has recognized the importance of enabling robots to interact with teams. Human teams rely on effective communication for successful 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.

Help or Hindrance: Understanding the Impact of Robot Communication in Action Teams

TL;DR

The paper investigates how multimodal robot communication affects team workload and perception in time-sensitive action-team contexts using a robotic crash cart in medical simulations. It employs a Wizard-of-Oz RCC delivering speech and light cues across three conditions, measuring outcomes with NASA-TLX and TAM. Findings show that verbal object-search cues combined with visual reminders (C2) improve perceived usefulness and ease of use while reducing workload compared with unimodal or no feedback, underscoring the value of task- and space-aware communication. The work highlights the role of spatial dynamics and embodiment in HRI design and offers practical guidance for deploying collaborative robots in hospitals, search-and-rescue, and manufacturing, along with directions for adaptive multimodal strategies.

Abstract

The human-robot interaction (HRI) field has recognized the importance of enabling robots to interact with teams. Human teams rely on effective communication for successful 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.

Paper Structure

This paper contains 14 sections, 5 figures.

Table of Contents

  1. INTRODUCTION
  2. RELATED WORK
  3. Teamwork in Human-Robot Interaction
  4. Multimodal Interaction in HRI
  5. METHODOLOGY
  6. Robotic Platform
  7. Pilot Study
  8. Main Study
  9. Main Study Results
  10. Perceived Usefulness Results
  11. Perceived Ease of Use Results
  12. Workload Results
  13. DISCUSSION
  14. Conclusion

Figures (5)

  • Figure 1: Multimodal robot communication in human-robot teams.
  • Figure 2: System diagram of the robotic crash cart illustrating the user interface, processing via Raspberry Pi 4B using ROS, and multimodal outputs through light strips and audio signals.
  • Figure 3: The Robotic Crash Cart (RCC) was operated on a tablet using Wizard-of-Oz control driven by a Raspberry Pi that sent signals to a speaker and LED light strip to communicate with action teams.
  • Figure 4: Pilot study NASA-TLX workload scores.
  • Figure 5: Main study results: NASA-TLX (left), Perceived Usefulness (middle) and Perceived Ease of Use (right).