A Framework for Dynamic Situational Awareness in Human Robot Teams: An Interview Study

TL;DR

The paper tackles the problem of static SA assumptions in human–robot teaming by proposing a dynamic situational awareness (DSA) framework. It uses 16 semi-structured interviews across diverse HRT contexts to show that both required and actual SA vary over time due to contextual, human, and robot factors, producing five SA inefficiencies: latency, loss, inaccuracy, incompleteness, and excess SA. The study identifies drivers of these dynamics and outlines operator- and interface-initiated strategies to maintain SA alignment, highlighting implications for objective, time-adaptive SA estimation and user-adaptive interfaces. The work advances practical design guidance for more collaborative and effective HRTs and suggests directions for extending DS concepts to robot SA and team SA in future research.

Abstract

In human-robot teams, human situational awareness is the operator's conscious knowledge of the team's states, actions, plans and their environment. Appropriate human situational awareness is critical to successful human-robot collaboration. In human-robot teaming, it is often assumed that the best and required level of situational awareness is knowing everything at all times. This view is problematic, because what a human needs to know for optimal team performance varies given the dynamic environmental conditions, task context and roles and capabilities of team members. We explore this topic by interviewing 16 participants with active and repeated experience in diverse human-robot teaming applications. Based on analysis of these interviews, we derive a framework explaining the dynamic nature of required situational awareness in human-robot teaming. In addition, we identify a range of factors affecting the dynamic nature of required and actual levels of situational awareness (i.e., dynamic situational awareness), types of situational awareness inefficiencies resulting from gaps between actual and required situational awareness, and their main consequences. We also reveal various strategies, initiated by humans and robots, that assist in maintaining the required situational awareness. Our findings inform the implementation of accurate estimates of dynamic situational awareness and the design of user-adaptive human-robot interfaces. Therefore, this work contributes to the future design of more collaborative and effective human-robot teams.

Figures (19)

• Figure 1: Proposed framework demonstrating the gaps between required and actual situational awareness (SA) within dynamic mission contexts
• Figure 2: Contextual, human and robot-related factors affect the dynamic nature of required and actual situational awareness (SA), contributing to dynamic situational awareness gaps
• Figure 3: Contextual factors affecting the required SA. Factors in red contribute to an increase in required SA when their value increases, while the factor in blue contributes to a decrease in required SA when its value increases. The dashed arrow illustrates that "safety criticality" depends on "task criticality and challenge".
• Figure 4: Robot-related factors affecting the required SA. The factor in red increases the required SA, while the factors in blue decrease the required SA. Factors in grey indicate mixed trends.
• Figure 5: Human factors affecting the required SA. Both factors in blue decrease the required SA. The factor in white is not quantifiable, thus cannot be associated with increased or decreased required SA.