Research on cooperative algorithm of UGV-UAV based on TERRA in complex environment

The utilization of heterogeneous multi-agent systems for planetary exploration represents a significant advancement in the field of future deep space exploration. The author’s research investigates a set of heterogeneous multi-agent systems, which include an Unmanned Ground Vehicle (UGV) and an Unmanned Aerial Vehicle (UAV), designed to explore a series of target points within a three-dimensional complex environment. In this 3D context, the complexity of environmental factors poses challenges, with terrain hazards being the primary concern that impacts UGV-UAV cooperative exploration. To facilitate the successful completion of target point exploration while minimizing risk, the authors proposes a cooperative search routing algorithm specifically tailored for UGV-UAV systems operating in complex environments. The algorithm capitalizes on the endurance advantages inherent to UGV alongside the functional benefits provided by UAVs; notably, it designates the UGV as a charging station for the UAV and positions the UAV as the principal detection device within this system to effectively accomplish detection tasks. Following the research framework established in the author’s research, it is essential first to define a set of target points within the 3D environment and subsequently project these points onto a 2D plane to identify docking locations for UGVs. These docking points are then re-projected into their corresponding positions in 3D space. The A* algorithm is employed to plan optimal paths between these UGV docking points within that three-dimensional context, thereby ensuring comprehensive exploration of all designated target points. Finally, the authors conducted simulation experiments in relation to Mars exploration. The authors developed a Mars exploration simulation platform based on virtual reality technology. This platform incorporates a physics engine designed to replicate Mars’s physical environment, enabling us to validate the effectiveness of the proposed system under conditions analogous to those found on Mars.

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Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering
Published
2026-03-31
DOI
https://doi.org/10.1177/09544100261434427
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Research on cooperative algorithm of UGV-UAV based on TERRA in complex environment

Xiao Li, Yueyue Li, Wanan Zhu, Ji Qi et al.
Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering
Distributed Control Multi-Agent Systems
article

Research on cooperative algorithm of UGV-UAV based on TERRA in complex environment

Xiao Li, Yueyue Li, Wanan Zhu, Ji Qi, Hao Wu
article en

Abstract

The utilization of heterogeneous multi-agent systems for planetary exploration represents a significant advancement in the field of future deep space exploration. The author’s research investigates a set of heterogeneous multi-agent systems, which include an Unmanned Ground Vehicle (UGV) and an Unmanned Aerial Vehicle (UAV), designed to explore a series of target points within a three-dimensional complex environment. In this 3D context, the complexity of environmental factors poses challenges, with terrain hazards being the primary concern that impacts UGV-UAV cooperative exploration. To facilitate the successful completion of target point exploration while minimizing risk, the authors proposes a cooperative search routing algorithm specifically tailored for UGV-UAV systems operating in complex environments. The algorithm capitalizes on the endurance advantages inherent to UGV alongside the functional benefits provided by UAVs; notably, it designates the UGV as a charging station for the UAV and positions the UAV as the principal detection device within this system to effectively accomplish detection tasks. Following the research framework established in the author’s research, it is essential first to define a set of target points within the 3D environment and subsequently project these points onto a 2D plane to identify docking locations for UGVs. These docking points are then re-projected into their corresponding positions in 3D space. The A* algorithm is employed to plan optimal paths between these UGV docking points within that three-dimensional context, thereby ensuring comprehensive exploration of all designated target points. Finally, the authors conducted simulation experiments in relation to Mars exploration. The authors developed a Mars exploration simulation platform based on virtual reality technology. This platform incorporates a physics engine designed to replicate Mars’s physical environment, enabling us to validate the effectiveness of the proposed system under conditions analogous to those found on Mars.

Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering
Aviation Industry Corporation of China (China) (CN), Shenyang Aerospace University (CN), Craft Group (China) (CN), Royal Aeronautical Society (GB), Institute of Aviation Medicine (CZ), Naval Aeronautical and Astronautical University (CN)
Natural Science Foundation of Shenyang City
Openalex Percentile: Top 26%
Distributed Control Multi-Agent Systems
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