Felix Gervits

Team Communication as a Collaborative Process

Communication channels can reveal a great deal of information about the effectiveness of a team. This is particularly relevant for teams operating in performance settings such as medical groups, military squads, and mixed human-robot teams. Currently, it is not known how various factors including coordination strategy, speaker role, and time pressure affect communication in collaborative tasks. The purpose of this paper is to systematically explore how these factors interact with team discourse in order to better understand effective communication patterns. In our analysis of a corpus of remote task-oriented dialogue (CReST corpus), we found that a variety of linguistic- and dialogue-level features were influenced by time pressure, speaker role, and team effectiveness. We also found that effective teams had a higher speech rate, and used specific grounding strategies to improve efficiency and coordination under time pressure. These results inform our understanding of the various factors that influence team communication, and highlight ways in which effective teams overcome constraints on their communication channels.

Shared Mental Models to Support Distributed Human-Robot Teaming in Space

Effective human-robot interaction (HRI) is a critical requirement for current and future space operations. However, given the limitations of autonomous technologies, robots are not yet capable of coordinating with human crew as peers under real-world mission constraints. Due to the complexity inherent in space robotics operations, it is crucial that robots are able to coordinate the various aspects of human-robot teaming and the task at hand. In this paper, we extend our Shared Mental Model (SMM) interaction framework to show how it can be used to overcome some of the challenges inherent in distributed HRI and facilitate coordination in space robotics teams. Since this framework has not yet been implemented in real systems, we conducted an exploratory study to identify potential benefits that the SMM mechanisms can afford in a task domain involving simulated free-flying robot assistants on a spacecraft. We found that the SMM framework offers advantages to task performance and team efficiency due to its support of shared knowledge representations, however these benefits do not seem to reduce workload or improve other subjective measures. The significance of these findings for future space operations is discussed, as are directions for future research.

Disfluency Handling for Robot Teammates

Findings from the Psycholinguistic literature have shown that disfluencies may serve a coordination function for both the speaker and the listener. Given that disfluencies are common in spontaneous speech, particularly in high workload tasks, it is important that robots are able to utilize the information contained in disfluencies to improve interaction. My work focuses on this goal of improving coordination in human-robot teams through the detection and utilization of disfluent speech. I use a multi-disciplinary approach that involves conducting empirical studies to investigate how disfluencies influence grounding and coordination in teams, and using the results of these studies to inform the design of computational mechanisms that enable robots to detect and utilize disfluencies in situated interaction. In this paper, I present the results of an empirical investigation and show how the findings are being used to develop computational mechanisms for disfluency handling. Future work involving the integration of these mechanisms in a cognitive robotic architecture is also discussed.

Exploring Coordination in Human-Robot Teams in Space

Human-robot teams in space environments are difficult to evaluate, in large part because performance of these teams is influenced by a variety of factors, including team size, structure, and composition. We introduce and describe a novel experimental framework that is sensitive to these factors, and that serves as a testbed to facilitate the study of human-robot teaming in space. We also report on the results of a preliminary study in this framework that involves a human interacting with a simulated Mars rover. Our findings show that people exhibited great variation in strategy and performance, and point to the role that decision-making and task-switching may have played in this result. This study is the first in a larger effort to develop a rich multimodal corpus and to investigate various dimensions of teaming in this domain.