A Cognitive Human Model for Virtual Commissioning of Dynamic Human-Robot Teams

Riedelbauch, Dominik; Luthardt-Bergmann, Daniel; Henrich, Dominik

doi:10.1109/irc52146.2021.00011

Cited by 4 publications

(3 citation statements)

References 22 publications

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“…trust [17,45,48,57,73,77] physical attribute of the robot [39,70,72] user interface [37,38,42,46,51,60,63,64,73] dynamic of the situation [75] acceptance [17,57,71,77] robot errors [36,55] control modality [37,65,71] task complexity [36,55,66,69,80] human characteristics [39] trajectory and movement [53,55,78] feedback [39,48,51,52,62,72] design of workspace [39,73,77] physical workload [50] role of the robot [61,76,…”

Section: Human Factors Robot Factors Communication Factors Environmen...mentioning

confidence: 99%

“…Human-centred design is also discussed and suggested. For example, considerations for a more human-centred HRC design [17]; understanding the bidirectional nature of anticipatory actions and improving the accuracy of intent prediction [68]; using simulations to predict and plan for human behaviour and developing tools for coupling human models [50]; designing with consideration for operator states, appropriate task allocation, and the use of adaptive interfaces [45]; and designing collaborative system features that can adapt to individual user preferences and needs [72].…”

Section: Potential Solutionsmentioning

confidence: 99%

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What Affects Human Decision Making in Human–Robot Collaboration?: A Scoping Review

Liu,

Caldwell,

Rittenbruch

et al. 2024

Robotics

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The advent of Industry 4.0 has heralded advancements in Human–robot Collaboration (HRC), necessitating a deeper understanding of the factors influencing human decision making within this domain. This scoping review examines the breadth of research conducted on HRC, with a particular focus on identifying factors that affect human decision making during collaborative tasks and finding potential solutions to improve human decision making. We conducted a comprehensive search across databases including Scopus, IEEE Xplore and ACM Digital Library, employing a snowballing technique to ensure the inclusion of all pertinent studies, and adopting the PRISMA Extension for Scoping Reviews (PRISMA-ScR) for the reviewing process. Some of the important aspects were identified: (i) studies’ design and setting; (ii) types of human–robot interaction, types of cobots and types of tasks; (iii) factors related to human decision making; and (iv) types of user interfaces for human–robot interaction. Results indicate that cognitive workload and user interface are key in influencing decision making in HRC. Future research should consider social dynamics and psychological safety, use mixed methods for deeper insights and consider diverse cobots and tasks to expand decision-making studies. Emerging XR technologies offer the potential to enhance interaction and thus improve decision making, underscoring the need for intuitive communication and human-centred design.

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Section: Human Factors Robot Factors Communication Factors Environmen...mentioning

confidence: 99%

Section: Potential Solutionsmentioning

confidence: 99%

What Affects Human Decision Making in Human–Robot Collaboration?: A Scoping Review

Liu,

Caldwell,

Rittenbruch

et al. 2024

Robotics

View full text Add to dashboard Cite

show abstract

“…Recent models include behaviours such as inter-agent communication and leaving the workstation for a break [261], e.g. by relating transition probabilities in a Markov Decision Process to human fatigue [261], [262] or frustration [261] accumulated over time.…”

Section: ) Virtual Human-in-the-loop Virtual Commissioningmentioning

confidence: 99%

Benchmarking Teamwork of Humans and Cobots—An Overview of Metrics, Strategies, and Tasks

2023

Self Cite

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Human-robot teaming receives an ever-increasing level of attention in research, development and industry. Novel approaches to task sharing in hybrid teams range from optimized schedules to intelligent cobot assistants with a high degree of autonomy. These approaches must prove their usefulness and benefits compared to manual work or full automation -particularly when it comes to assessing their potential for productive industrial use. This leverages demand for standardized, repeatable benchmarks to compare approaches and measure improvements in a reproducible way. Designing such benchmarks is challenging as numerous aspects, from safety considerations to human factors and team performance, must be considered. This survey seeks to contribute to the future development of benchmarks for the field of collaborative assembly, handling, and industrial cobot applications by giving a comprehensive overview of relevant metrics, evaluation strategies, and tasks for human-robot teams.

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Generation and retrieval of procedural memory using natural intelligence for an articulated robot

Chattoraj

Kalganova

2023

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)

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A Cognitive Human Model for Virtual Commissioning of Dynamic Human-Robot Teams

Cited by 4 publications

References 22 publications

What Affects Human Decision Making in Human–Robot Collaboration?: A Scoping Review

What Affects Human Decision Making in Human–Robot Collaboration?: A Scoping Review

Benchmarking Teamwork of Humans and Cobots—An Overview of Metrics, Strategies, and Tasks

Generation and retrieval of procedural memory using natural intelligence for an articulated robot

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