Attention Allocation for Human Multi-Robot Control: Cognitive Analysis based on Behavior Data and Hidden States

Human multi-robot interaction exploits both the human operator’s high-level decision-making skills and the robotic agents’ vigorous computing and motion abilities. While controlling multi-robot teams, an operator’s attention must constantly shift between individual robots to maintain sufficient situation awareness. To conserve an operator’s attentional resources, a robot with self reflect capability on its abnormal status can help an operator focus her attention on emergent tasks rather than unneeded routine checks. With the proposing self-reflect aids, the human-robot interaction becomes a queuing framework, where the robots act as the clients to request for interaction and an operator acts as the server to respond these job requests. This paper examined two types of queuing schemes, the self-paced Open-queue identifying all robots’ normal/abnormal conditions, whereas the forced-paced shortest-job-first (SJF) queue showing a single robot’s request at one time by following the SJF approach. As a robot may miscarry its experienced failures in various situations, the effects of imperfect automation were also investigated in this paper. The results suggest that the SJF attentional scheduling approach can provide stable performance in both primary (locate potential targets) and secondary (resolve robots’ failures) tasks, regardless of the system’s reliability levels. However, the conventional results (e.g., number of targets marked) only present little information about users’ underlying cognitive strategies and may fail to reflect the user’s true intent. As understanding users’ intentions is critical to providing appropriate cognitive aids to enhance task performance, a Hidden Markov Model (HMM) is used to examine operators’ underlying cognitive intent and identify the unobservable cognitive states. The HMM results demonstrate fundamental differences among the queuing mechanisms and reliability conditions. The findings suggest that HMM can be helpful in investigating the use of human cognitive resources under multitasking environments

Fly with me : algorithms and methods for influencing a flock

As robots become more affordable, they will begin to exist in the world in greater quantities. Some of these robots will likely be designed to act as components in specific teams. These teams could work on tasks that are too large or complex for a single robot - or that are merely more efficiently accomplished by a team - such as surveillance in a large building or product delivery to packers in a warehouse. Multiagent systems research studies how these teams are formed and how they work together. Ad hoc teamwork, a newer area of multiagent systems research, studies how new robots can join these pre-existing teams and assist the team in accomplishing its goal. This dissertation extends and applies research in ad hoc teamwork towards the general area of flocking, which is an emergent swarm behavior. In particular, the work in this dissertation considers how ad hoc agents - called influencing agents in this dissertation - can join a flock, be recognized by the rest of the flock as part of the flock, influence the flock towards particular behaviors through their own behavior, and then separate from the flock. Specifically, the primary research question addressed in this dissertation is How can influencing agents be utilized in various types of flocks to influence the flock towards a particular behavior? In order to address this research question, this dissertation makes six main types of contributions. First, this dissertation formalizes the problem of using influencing agents to influence a flock. Second, this dissertation contributes and analyzes algorithms for influencing a flock to a desired orientation. Third, this dissertation presents methods for determining how to best add influencing agents to a flock. Fourth, this dissertation provides methods by which influencing agents can join and then leave a flock in motion. Fifth, this dissertation evaluates some of the influencing agent algorithms on a robot platform. Sixth, although the majority of this dissertation assumes the influencing agents will join a flock that behaves similarly to European starlings, this dissertation also provides insight into when and how its algorithms are generalizable to other types of flocks as well as to general teamwork and coordination research. All of the methods presented in this dissertation are empirically evaluated using a simulator that can support large flocks.Computer Science

Leadership in an Artificial Intelligence Era

The current literature review attempts to combine the two topics “leadership” and “artificial intelligence” by highlighting the main perspectives in the research field of Leadership in Industry 4.0, dominated by Artificial Intelligence (AI)-based technologies. The current literature review identifies the three main directions of the scholarly and practitioner research: 1) AI as an additional assistance to current leadership functions (enhancement perspective); 2) AI to replace followers and leaders (replacement perspective); and 3) AI as “an oversold idea” (skeptical perspective). This literature review addresses a lack of substantial literature review and empirical data providing a balanced view of different perspectives on AI-based technologies’ influence on the leadership of modern organizations. The objective of the current paper is to conduct an initial literature review on Leadership in Industry 4.0, dominated by AI-based technologies, with emphasis on the AI-based technologies’ influence on the leadership of modern organizations. The current literature review attempts to answer the following research question: What are the main perspectives of the scholarly and practitioner research directions in the period 2010-2020 in the field of Leadership in an Artificial Intelligence era?” Possible contribution of this paper is that identified perspectives could become a basis for future empirical research by the author and other scholars and practitioners in the field. Keywords: leadership; Industry 4.0; artificial intelligenc

Asynchronous control with ATR for large robot teams

In this paper, we discuss and investigate the advantages of an asynchronous display, called "image queue", tested for an urban search and rescue foraging task. The image queue approach mines video data to present the operator with a relevant and comprehensive view of the environment by selecting a small number of images that together cover large portions of the area searched. This asynchronous approach allows operators to search through a large amount of data gathered by autonomous robot teams, and allows comprehensive and scalable displays to obtain a network-centric perspective for unmanned ground vehicles (UGVs). In the reported experiment automatic target recognition (ATR) was used to augment utilities based on visual coverage in selecting imagery for presentation to the operator. In the cued condition a box was drawn in the region in which a possible target was detected. In the no-cue condition no box was drawn although the target detection probability continued to play a role in the selection of imagery. We found that operators using the image queue displays missed fewer victims and relied on teleoperation less often than those using streaming video. Image queue users in the no-cue condition did better in avoiding false alarms and reported lower workload than those in the cued condition. Copyright 2011 by Human Factors and Ergonomics Society, Inc. All rights reserved

User involvement in healthcare technology development and assessment: Structured literature review

Purpose – Medical device users are one of the principal stakeholders of medical device technologies. User involvement in medical device technology development and assessment is central to meet their needs. Design/methodology/approach – A structured review of literature, published from 1980 to 2005 in peer-reviewed journals, was carried out from social science perspective to investigate the practice of user involvement in the development and assessment of medical device technologies. This was followed by qualitative thematic analysis. Findings – It is found that users of medical devices include clinicians, patients, carers and others. Different kinds of medical devices are developed and assessed by user involvement. The user involvement occurs at different stages of the medical device technology lifecycle and the degree of user involvement is in the order of design stage > testing and trials stage > deployment stage > concept stage. Methods most commonly used for capturing users’ perspectives are usability tests, interviews and questionnaire surveys. Research limitations/implications – We did not review the relevant literature published in engineering, medical and nursing fields, which might have been useful. Practical implications – Consideration of the users’ characteristics and the context of medical device use is critical for developing and assessing medical device technologies from users’ perspectives. Originality/value – This study shows that users of medical device technologies are not homogeneous but heterogeneous, in several aspects, and their needs, skills and working environments vary. This is important consideration for incorporating users’ perspectives in medical device technologies. Paper type: Literature review