Human-Robot Teaming Directions for Dull, Dirty and Dangerous Domains

Human-robot interaction has emerged over the last few decades as a critical aspect of deploying robot systems and numerous important challenges have been addressed; however, the deployment of heterogeneous robot systems that team with humans to reliably complete tasks in real dull, dirty and dangerous domains remains nascent. These domains, such as forestry management, infrastructure inspection and demolition, or agricultural crop management suffer from severe workforce shortages and high workforce turnover. These jobs also often require a skilled workforce and are some of the most dangerous. Robots can team with humans to increase safety and productivity, while reducing costs and not taking critical skilled labor jobs. Recent trends have moved the field forward for well-structured laboratory, home or office environments, however the resulting human-robot teaming technologies developed for these environments typically do not translate to the unstructured, uncertain and dynamic field environments represented by the dull, dirty and dangerous domains. Making the necessary leaps forward requires an increased focus on human-robot teaming, robot technologies, and the associated necessary field work. This keynote will focus on critical research directions for the next decade plus. These challenges will require systems level developments that support intelligent autonomy and teaming capabilities as well as the breadth of human-robot interaction roles - from supervisors to bystanders [1]–[3]. Future teams for these domains will span single human-single robot systems to highly heterogeneous multiple human-multiple robot teams that cooperative heavily across all team members and have a mix of capabilities to support humans, while also keeping humans safe.

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Publication Details

Published
2025-03-04
DOI
https://doi.org/10.1109/hri61500.2025.10974142
Citations
3
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
7.32
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article

Human-Robot Teaming Directions for Dull, Dirty and Dangerous Domains

Julie A. Adams
3 citations
Human-Automation Interaction and Safety
7.32
article

Human-Robot Teaming Directions for Dull, Dirty and Dangerous Domains

Julie A. Adams
article en
3 citations

Abstract

Human-robot interaction has emerged over the last few decades as a critical aspect of deploying robot systems and numerous important challenges have been addressed; however, the deployment of heterogeneous robot systems that team with humans to reliably complete tasks in real dull, dirty and dangerous domains remains nascent. These domains, such as forestry management, infrastructure inspection and demolition, or agricultural crop management suffer from severe workforce shortages and high workforce turnover. These jobs also often require a skilled workforce and are some of the most dangerous. Robots can team with humans to increase safety and productivity, while reducing costs and not taking critical skilled labor jobs. Recent trends have moved the field forward for well-structured laboratory, home or office environments, however the resulting human-robot teaming technologies developed for these environments typically do not translate to the unstructured, uncertain and dynamic field environments represented by the dull, dirty and dangerous domains. Making the necessary leaps forward requires an increased focus on human-robot teaming, robot technologies, and the associated necessary field work. This keynote will focus on critical research directions for the next decade plus. These challenges will require systems level developments that support intelligent autonomy and teaming capabilities as well as the breadth of human-robot interaction roles - from supervisors to bystanders [1]–[3]. Future teams for these domains will span single human-single robot systems to highly heterogeneous multiple human-multiple robot teams that cooperative heavily across all team members and have a mix of capabilities to support humans, while also keeping humans safe.

Oregon State University (US)
Openalex Percentile: Top 3%
Human-Automation Interaction and Safety
7.32
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