Abstract
Team resilience affects both the cohesion and subsequent performance of that team. For human teams, resilience is tied to team learning, team flexibility, social capital, and collective efficacy. But for human-autonomy teams, resilience also includes cyber resilience and robust and adaptable robotic control. This work builds out the theory associated with resilience in human-autonomy teams, followed by a step-by-step procedure for developing a resilience subscale for measuring human-autonomy team cohesion.
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Notes
- 1.
A non-human intelligent agent is typically defined as “an autonomous entity which observes and acts upon an environment entity and directs its activity toward achieving goals” (Russell & Norvig, 2009, pg. 34). Non-human agents should have the following characteristics: autonomy, observation of the environment, action upon the environment, and direction of activity towards achieving certain goals (Chen & Barnes, 2014; Russell & Norvig, 2010).
- 2.
Any task or more specifically system with inputs (controls) and outputs (states) can be analyzed as a control system. As motion control is integral to nearly all robot tasks, following a trajectory will very often be a task or component thereof, but a task can be much broader including for example elements of manipulation.
- 3.
Note that we do not advocate that the explicit use of robust control is a necessary condition for achieving resilience. Many if not all control approaches seek to achieve robustness through more or less formal descriptions.
- 4.
This is a standard method of scale development and has been used recently in the development of human-autonomy team trust scales (Yagoda & Gillan, 2012; Schaefer, 2016). Lawshe’s protocol recommends 11 SMEs with a criterion set to 0.59 to ensure SME agreement is unlikely due to chance. The formula yields values ranging from +1 to –1, where positive values indicate at least half of the SMEs rated the item as extremely important.
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Acknowledgments
Research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-20-2-0250. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein. The authors thank the subject matter experts and reviewers for their helpful feedback. The authors also thank the scale development team: Drs., Sean Fitzhugh, Danny Forster, Shan Lakhmani, Erica Rovira and Cadet Jordan Blackmon.
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Berg, S., Neubauer, C., Robison, C., Kroninger, C., Schaefer, K.E., Krausman, A. (2021). Exploring Resilience and Cohesion in Human-Autonomy Teams: Models and Measurement. In: Zallio, M., Raymundo Ibañez, C., Hernandez, J.H. (eds) Advances in Human Factors in Robots, Unmanned Systems and Cybersecurity. AHFE 2021. Lecture Notes in Networks and Systems, vol 268. Springer, Cham. https://doi.org/10.1007/978-3-030-79997-7_15
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