Open Human-Robot Collaboration Systems (OHRCS): A Research Perspective

Human-robot collaboration (HRC) is the paradigm of humans and robots working synergistically in a shared workspace toward common goals. Prior research models such collaborative scenarios as multiagent systems composed of a fixed number of agents. Such models where the number and type of agents remain constant throughout, are termed closed systems. Conversely, a human-robot collaborative where the team size dynamically changes during the task is called an open HRC system (OHRCS). OHRCS allows for a realistic representation of human-robot collaboration by allowing agents to join or leave the task as needed. In this paper, we posit that many real-world HRC scenarios are better modeled as OHRCS. We present our vision of OHRC, present potential applications, examine the benefits of openness in HRC, and provide some avenues for future research.

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Published
2024-10-28
DOI
https://doi.org/10.1109/cogmi62246.2024.00023
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
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article

Open Human-Robot Collaboration Systems (OHRCS): A Research Perspective

Prashant Doshi, Prasanth Sengadu Suresh, Diego Romeres, Siddarth Jain
Robot Manipulation and Learning
article

Open Human-Robot Collaboration Systems (OHRCS): A Research Perspective

Prashant Doshi, Prasanth Sengadu Suresh, Diego Romeres, Siddarth Jain
article en

Abstract

Human-robot collaboration (HRC) is the paradigm of humans and robots working synergistically in a shared workspace toward common goals. Prior research models such collaborative scenarios as multiagent systems composed of a fixed number of agents. Such models where the number and type of agents remain constant throughout, are termed closed systems. Conversely, a human-robot collaborative where the team size dynamically changes during the task is called an open HRC system (OHRCS). OHRCS allows for a realistic representation of human-robot collaboration by allowing agents to join or leave the task as needed. In this paper, we posit that many real-world HRC scenarios are better modeled as OHRCS. We present our vision of OHRC, present potential applications, examine the benefits of openness in HRC, and provide some avenues for future research.

University of Georgia (US), Mitsubishi Electric (United States) (US)
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Openalex Percentile: Top 69%
Robot Manipulation and Learning
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