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A ROS2-based Distributed Task Allocation Framework for Unmanned Vehicles: From Multi-waypoint Task Modeling to HITL Evaluation.

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Název: A ROS2-based Distributed Task Allocation Framework for Unmanned Vehicles: From Multi-waypoint Task Modeling to HITL Evaluation.
Autoři: Park, Hwan-Yong, Kim, Yeong-Ung, Park, Jun-Oh, Bae, Yoo-Bin
Zdroj: International Journal of Control, Automation & Systems; Dec2025, Vol. 23 Issue 12, p3513-3524, 12p
Abstrakt: This paper presents a distributed task allocation framework for multiple unmanned vehicles on the robot operating system 2 (ROS2) platform. The framework incorporates a generalized multi-waypoint task model, in which each task is defined as a sequence of waypoints generated from parameterized operational modes, enabling flexible representation of complex missions. A mission planning computer is developed to automatically generate such tasks and manage them in real time via a graphical user interface. Based on the task model, two representative task allocation algorithms, the asynchronous consensus-based bundle algorithm (ACBBA) and the distributed auction algorithm (DAA), are implemented within the distributed framework as modular ROS2 nodes. The algorithms are evaluated in hardware-in-the-loop (HITL) simulation with three mission scenarios and benchmarked against the global optimal solution. Simulation results empirically validate that DAA achieves near-optimal performance in a wide area search (WAS) scenario, while ACBBA provides robust performance in multi view observation (MVO) and maneuvering by altitude (MA) scenarios. To facilitate better understanding of the HITL simulation results, we provide demonstration videos at https://www.youtube.com/playlist?list=PLUIBjqIFRraEkQdp1zQHSRwhXDAeJjZ2D. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Control, Automation & Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: A ROS2-based Distributed Task Allocation Framework for Unmanned Vehicles: From Multi-waypoint Task Modeling to HITL Evaluation.
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  Data: <searchLink fieldCode="AR" term="%22Park%2C+Hwan-Yong%22">Park, Hwan-Yong</searchLink><br /><searchLink fieldCode="AR" term="%22Kim%2C+Yeong-Ung%22">Kim, Yeong-Ung</searchLink><br /><searchLink fieldCode="AR" term="%22Park%2C+Jun-Oh%22">Park, Jun-Oh</searchLink><br /><searchLink fieldCode="AR" term="%22Bae%2C+Yoo-Bin%22">Bae, Yoo-Bin</searchLink>
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  Data: International Journal of Control, Automation & Systems; Dec2025, Vol. 23 Issue 12, p3513-3524, 12p
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper presents a distributed task allocation framework for multiple unmanned vehicles on the robot operating system 2 (ROS2) platform. The framework incorporates a generalized multi-waypoint task model, in which each task is defined as a sequence of waypoints generated from parameterized operational modes, enabling flexible representation of complex missions. A mission planning computer is developed to automatically generate such tasks and manage them in real time via a graphical user interface. Based on the task model, two representative task allocation algorithms, the asynchronous consensus-based bundle algorithm (ACBBA) and the distributed auction algorithm (DAA), are implemented within the distributed framework as modular ROS2 nodes. The algorithms are evaluated in hardware-in-the-loop (HITL) simulation with three mission scenarios and benchmarked against the global optimal solution. Simulation results empirically validate that DAA achieves near-optimal performance in a wide area search (WAS) scenario, while ACBBA provides robust performance in multi view observation (MVO) and maneuvering by altitude (MA) scenarios. To facilitate better understanding of the HITL simulation results, we provide demonstration videos at https://www.youtube.com/playlist?list=PLUIBjqIFRraEkQdp1zQHSRwhXDAeJjZ2D. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal of Control, Automation & Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Dec2025
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