Cooperative Interactive Distributed Guidance on Mobile Devices

Mobiles device are quickly becoming an indispensable part of our society. Equipped with numerous communication capabilities, they are increasingly being examined as potential tools for civilian and military usage to aide in distributed remote collaboration for dynamic decision making and physical task completion. With an ever growing mobile workforce, the need for remote assistance in aiding field workers who are confronted with situations outside their expertise certainly increases. Enhanced capabilities in using mobile devices could significantly improve numerous components of a task\u27s completion (i.e. accuracy, timing, etc.). This dissertation considers the design of mobile implementation of technology and communication capabilities to support interactive collaboration between distributed team members. Specifically, this body of research seeks to explore and understand how various multimodal remote assistances affect both the human user\u27s performance and the mobile device\u27s effectiveness when used during cooperative tasks. Additionally, power effects are additionally studied to assess the energy demands on a mobile device supporting multimodal communication. In a series of applied experiments and demonstrations, the effectiveness of a mobile device facilitating multimodal collaboration is analyzed through both empirical data collection and subjective exploration. The utility of the mobile interactive system and its configurations are examined to assess the impact on distributed task performance and collaborative dialogue between pairs. The dissertation formulates and defends an argument that multimodal communication capabilities should be incorporated into mobile communication channels to provide collaborating partners salient perspectives with a goal of reaching a mutual understanding of task procedures. The body of research discusses the findings of this investigation and highlight these findings they may influence future mobile research seeking to enhance interactive distributed guidance

Learning Sciences Beyond Cognition: Exploring Student Interactions in Collaborative Problem Solving

Composed of insightful essays from top figures in their respective fields, the book also shows how a thorough understanding of this critical discipline all but ensures better decision making when it comes to education

Advances in Human-Robot Interaction

Rapid advances in the field of robotics have made it possible to use robots not just in industrial automation but also in entertainment, rehabilitation, and home service. Since robots will likely affect many aspects of human existence, fundamental questions of human-robot interaction must be formulated and, if at all possible, resolved. Some of these questions are addressed in this collection of papers by leading HRI researchers

Are you there? : Presence in collaborative distance work

doi linkki ei toimi 31.1.2022, ilmoitettu lehteen/USAlready before the pandemic, digitally mediated collaborative work and communication were perceived as challenging. We investigate the attitudes towards emerging technologies and for transforming practises in workplaces. The focus lies on understanding the readiness for appropriating emotional tracking on presence and support for collaboration. The research-based design framework allowed to combine the various perspectives of the transdisciplinary team. Methods included participatory design, design thinking, contextual inquiry and prototype testing for enhancing presence while working with shared objects in video conferencing to explore the appropriation of tools. The findings revealed four indications: 1) awareness of interlocutors’ presence during synchronous communication is crucial. 2) Emotion and behaviour tracking raises concerns about privacy and personal control over what is displayed to others, and technology could be simpler non-distracting the work at hand. 3) The prototype was found to enhance the feeling of presence without disturbing work at hand, and 4) appropriation requires a step-by-step approach.Peer reviewe

Interactive Execution Monitoring of Agent Teams

There is an increasing need for automated support for humans monitoring the activity of distributed teams of cooperating agents, both human and machine. We characterize the domain-independent challenges posed by this problem, and describe how properties of domains influence the challenges and their solutions. We will concentrate on dynamic, data-rich domains where humans are ultimately responsible for team behavior. Thus, the automated aid should interactively support effective and timely decision making by the human. We present a domain-independent categorization of the types of alerts a plan-based monitoring system might issue to a user, where each type generally requires different monitoring techniques. We describe a monitoring framework for integrating many domain-specific and task-specific monitoring techniques and then using the concept of value of an alert to avoid operator overload. We use this framework to describe an execution monitoring approach we have used to implement Execution Assistants (EAs) in two different dynamic, data-rich, real-world domains to assist a human in monitoring team behavior. One domain (Army small unit operations) has hundreds of mobile, geographically distributed agents, a combination of humans, robots, and vehicles. The other domain (teams of unmanned ground and air vehicles) has a handful of cooperating robots. Both domains involve unpredictable adversaries in the vicinity. Our approach customizes monitoring behavior for each specific task, plan, and situation, as well as for user preferences. Our EAs alert the human controller when reported events threaten plan execution or physically threaten team members. Alerts were generated in a timely manner without inundating the user with too many alerts (less than 10 percent of alerts are unwanted, as judged by domain experts)

Concept of a Robust & Training-free Probabilistic System for Real-time Intention Analysis in Teams

Die Arbeit beschäftigt sich mit der Analyse von Teamintentionen in Smart Environments (SE). Die fundamentale Aussage der Arbeit ist, dass die Entwicklung und Integration expliziter Modelle von Nutzeraufgaben einen wichtigen Beitrag zur Entwicklung mobiler und ubiquitärer Softwaresysteme liefern können. Die Arbeit sammelt Beschreibungen von menschlichem Verhalten sowohl in Gruppensituationen als auch Problemlösungssituationen. Sie untersucht, wie SE-Projekte die Aktivitäten eines Nutzers modellieren, und liefert ein Teamintentionsmodell zur Ableitung und Auswahl geplanten Teamaktivitäten mittels der Beobachtung mehrerer Nutzer durch verrauschte und heterogene Sensoren. Dazu wird ein auf hierarchischen dynamischen Bayes’schen Netzen basierender Ansatz gewählt