To forge effective collaborations with humans, robots require the capacity to understand and predict the behaviors of their human counterparts. There is a growing body of computational research on human modeling for human-robot interaction (HRI). However, a key bottleneck in conducting this research is the relative lack of data of cognitive states -- like intent, workload, and trust -- which undeniably affect human behavior. Despite their significance, these states are elusive to measure, making the assembly of datasets a challenge and hindering the progression of human modeling techniques. To help address this, we first introduce Rescue World for Teams (RW4T): a configurable testbed to simulate disaster response scenarios requiring human-robot collaboration. Next, using RW4T, we curate a multimodal dataset of human-robot behavior and cognitive states in dyadic human-robot collaboration. This RW4T dataset includes state, action and reward sequences, and all the necessary data to replay a visual task execution. It further contains psychophysiological metrics like heart rate and pupillometry, complemented by self-reported cognitive state measures. With data from 20 participants, each undertaking five human-robot collaborative tasks, this dataset (comprising of 100 unique trajectories) accompanied with the simulator can serve as a valuable benchmark for human behavior modeling.

The rise in artificial intelligence capabilities in autonomy-enabled systems and robotics has pushed research to address the unique nature of human-autonomy team collaboration. The goal of these advanced technologies is to enable rapid decision-making, enhance situation awareness, promote shared understanding, and improve team dynamics. Simultaneously, use of these technologies is expected to reduce risk to those who collaborate with these systems. Yet, for appropriate human-autonomy teaming to take place, especially as we move beyond dyadic partnerships, proper calibration of team trust is needed to effectively coordinate interactions during high-risk operations. But to meet this end, critical measures of team trust for this new dynamic of human-autonomy teams are needed. This article seeks to expand on trust measurement principles and the foundation of human-autonomy teaming to propose a “toolkit” of novel methods that support the development, maintenance, and calibration of trust in human-autonomy teams operating within uncertain, risky, and dynamic environments.

Multimodal interaction technologies have enabled new applications for training interpersonal skills such as public speaking. Various training paradigms have been proposed, most of them relying on some form of graphical feedback provided to the trainee in real-time during their training or after training using an after-action review tool. Another paradigm consists of using virtual characters to provide feedback through their behavior during simulated social interactions. Preliminary studies have started to explore the effectiveness of these different training paradigms; however, these have not investigated the impact of individual differences on which interaction paradigm is more efficient or motivating for different populations of users. In this article, we explore the impact of personality, public speaking anxiety, and immersive tendencies on the experiences of users training public speaking with an interactive virtual audience system providing realtime feedback through virtual audience behavior as well as delayed feedback with an after-action review tool. We found that these three factors impacted different output measures of user experience and user ratings of the system's quality.

The effects of oxytocin on facial emotional expressivity were investigated in individuals with schizophrenia and age-matched healthy controls during the completion of a Social Judgment Task (SJT) with a double-blind, placebo-controlled, cross-over design. Although pharmacological interventions exist to help alleviate some symptoms of schizophrenia, currently available agents are not effective at improving the severity of blunted facial affect. Participant facial expressivity was previously quantified from video recordings of the SJT using a well-validated manual approach (Facial Expression Coding System; FACES). We confirm these findings using an automated computer-based approach. Using both methods we found that the administration of oxytocin significantly increased total facial expressivity in individuals with schizophrenia and increased facial expressivity at trend level in healthy controls. Secondary analysis showed that oxytocin also significantly increased the frequency of negative valence facial expressions in individuals with schizophrenia but not in healthy controls and that oxytocin did not significantly increase positive valence facial expressions in either group. Both manual coding and automatic facial analysis revealed the same pattern of findings. Considering manual annotation can be expensive and time-consuming, these results suggest that automatic facial analysis may be an efficient and cost-effective alternative to currently utilized manual approaches and may be ready for use in clinical settings.

It is commonly known that a relationship exists between the human voice and various emotional states. Past studies have demonstrated changes in a number of vocal features, such as fundamental frequency f0 and peakSlope, as a result of varying emotional state. These voice characteristics have been shown to relate to emotional load, vocal tension, and, in particular, stress. Although much research exists in the domain of voice analysis, few studies have assessed the relationship between stress and changes in the voice during a dyadic team interaction. The aim of the present study was to investigate the multimodal interplay between speech and physiology during a high-workload, high-stress team task. Specifically, we studied task-induced effects on participants' vocal signals, specifically, the f0 and peakSlope features, as well as participants' physiology, through cardiovascular measures. Further, we assessed the relationship between physiological states related to stress and changes in the speaker's voice. We recruited participants with the specific goal of working together to diffuse a simulated bomb. Half of our sample participated in an "Ice Breaker" scenario, during which they were allowed to converse and familiarize themselves with their teammate prior to the task, while the other half of the sample served as our "Control". Fundamental frequency (f0), peakSlope, physiological state, and subjective stress were measured during the task. Results indicated that f0 and peakSlope significantly increased from the beginning to the end of each task trial, and were highest in the last trial, which indicates an increase in emotional load and vocal tension. Finally, cardiovascular measures of stress indicated that the vocal and emotional load of speakers towards the end of the task mirrored a physiological state of psychological "threat".

Here we describe the design and usability evaluation of a mixed reality prototype to simulate the role of a tank platoon leader, who is an individual who not only is a tank commander, but also directs a platoon of three other tanks with their own respective tank commanders. The domain of tank commander training has relied on physical simulators of the actual Abrams tank and encapsulates the whole crew. The TALK-ON system we describe here focuses on training communication skills of the leader in a simulated tank crew. We report results from a usability evaluation and discuss how they will inform our future work for collective tank training.

Team cohesion has been suggested to be a critical factor in emotional resilience following periods of stress. Team cohesion may depend on several factors including emotional state, communication among team members and even psychophysiological response. The present study sought to employ several multimodal techniques designed to investigate team behavior as a means of understanding resilience to stress. We recruited 40 subjects to perform a cooperative-task in gender-matched, two-person teams. They were responsible for working together to meet a common goal, which was to successfully disarm a simulated bomb. This high-workload task requires successful cooperation and communication among members. We assessed several behaviors that relate to facial expression, word choice and physiological responses (i.e., heart rate variability) within this scenario. A manipulation of an â€oeice breakerâ€❝ condition was used to induce a level of comfort or familiarity within the team prior to the task. We found that individuals in the â€oeice breakerâ€❝ condition exhibited better resilience to subjective stress following the task. These individuals also exhibited more insight and cognitive speech, more positive facial expressions and were also able to better regulate their emotional expression during the task, compared to the control.