Fei Gao
ABSTRACT
Simultaneously controlling increasing numbers of robots requires multiple operators working together as a team. Helping operators allocate attention among different robots and determining how to construct the human-robot team to promote performance and reduce workload are critical questions that must be answered in these settings. To this end, we investigated the effect of team structure and search guidance on operators' performance, subjective workload, work processes and communication. To investigate team structure in an urban search and rescue setting, we compared a pooled condition, in which team members shared control of 24 robots, with a sector condition, in which each team member control half of all the robots. For search guidance, a notification was given when the operator spent too much time on one robot and either suggested or forced the operator to change to another robot. A total of 48 participants completed the experiment with two persons forming one team. The results demonstrate that automated search guidance neither increased nor decreased performance. However, suggested search guidance decreased average task completion time in Sector teams. Search guidance also influenced operators' teleoperation behaviors. For team structure, pooled teams experienced lower subjective workload than sector teams. Pooled teams communicated more than sector teams, but sector teams teleoperated more than pool teams.
- Bertuccelli, L. F., Pellegrino, N. et al. 2010. Choice modeling of relook tasks for UAV search missions. American Control Conference (ACC), 2010.Google Scholar
- Crandall, J. W. and Cummings, M. L. 2007. Attention Allocation Efficiency in Human-UV Teams AIAA Infotech@Aerospace Conference, Rohnert Park, CA, 2007.Google Scholar
- Crandall, J. W., Goodrich, M. A., Olsen, D. R., Jr. and Nielsen, C. W. 2005. Validating human-robot interaction schemes in multitasking environments. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 35 (4). 438--449. Google ScholarDigital Library
- Farinelli, A., Scerri, P. and Tambe, M. 2003. Building large-scale robot systems: Distributed role assignment in dynamic, uncertain domains. iAAMAS'03 Workshop on Resources, role and task allocation in multiagent systems.Google Scholar
- Gladstein, D. L. 1984. Groups in Context: A Model of Task Group Effectiveness. Administrative Science Quarterly 29(4): 499--517.Google ScholarCross Ref
- Lewis, M., Polvichai, J. et al. 2006. Scaling-up Human Control for Large UAV Teams. The Human Factors of Remotely Piloted Vehicles. N. Cooke, Ed. New York, Elsevier: 237--250.Google Scholar
- Hart, S. G. and Staveland, L. E. 1998. Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. in Hancock, P. A. and Meshkati, N. eds. Human Mental Workload, North Holland Press, Amsterdam.Google Scholar
- Lewis, M., Wang, H. et al. 2011. Process and Performance in Human-Robot Teams. Journal of Cognitive Engineering and Decision Making 5(2): 186--208.Google ScholarCross Ref
- Lewis, M., Wang, H., Chien, S. Y., Velagapudi, P., Scerri, P. and Sycara, K. 2010. Choosing Autonomy Modes for Multirobot Search. Human Factors: The Journal of the Human Factors and Ergonomics Society, 52 (2). 225--233.Google ScholarCross Ref
- Lewis, M., Wang, J. and Hughes, S. 2007. USARSim: Simulation for the Study of Human-Robot Interaction. Journal of Cognitive Engineering and Decision Making, 1 (1). 98--120.Google ScholarCross Ref
- Macmillan, J., Entin, E. E. et al. 2004. Communication Overhead: The Hidden Cost of Team Cognition. Team Cognition: Understanding the Factors That Drive Process and Performance. E. Salas and S. M. Fiore, Ed., American Psychological Association (APA).Google Scholar
- Mouloua, M. and Parasuraman, R. 1996. Automation and Human Performance: Theory and Applications, CRC Press.Google Scholar
- Naylor, J. C. and Dickinson, T. L. 1969. Task structure, work structure, and team performance. Journal of Applied Psychology 53(10).Google ScholarCross Ref
- Salas, E. and Fiore, S. M. 2004. Team Cognition: Understanding the Factors That Drive Process and Performance, American Psychological Association (APA).Google ScholarCross Ref
- Salas, E., Sims D. E., et al. 2005. Is there a Big Five in Teamwork? Small Group Research 36(5): 555--599.Google ScholarCross Ref
- Wickens, C. D. and Hollands, J. G. 1999. Engineering Psychology and Human Performance, Pearson Education.Google Scholar
Index Terms
- Teamwork in controlling multiple robots
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