Safety-Aware UAV Formation Scheme for Guiding UGVs Through Obstacle-Laden Environments

Using unmanned aerial vehicle (UAV) formations to guide unmanned ground vehicles (UGVs) through unstructured obstacle-laden areas leads to highly efficient execution of tasks such as the transportation of supplies. However, existing methods fail to efficiently plan obstacle-avoidance strategies for the entire UAV-UGV swarm. Additionally, the formation controller and planner are isolated, resulting in the degradation of formation tracking accuracy, which presents potential security risks. This paper proposes a novel UAV formation scheme that integrates safe corridor (SC) generation, trajectory fitting, and formation tracking to ensure operational safety. The scheme employs a novel line-of-sight (LOS) mechanism to optimize A*-planned waypoints, generating the SC as an obstacle-avoidance strategy. A minimum snap trajectory is fitted to the optimized waypoints with SC constraints. Bridged by the trajectory, the scheme develops a rigid-graph-based controller (RGC) to track the planning result, enabling dynamic formation maneuvering within the SC. Consequently, the proposed UAV formation scheme achieves obstacle-avoidance guidance by restricting the UGVs to the formation projection. The validation results demonstrate that the proposed scheme exhibits enhanced robustness and superior planning capabilities compared to traditional methods.

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Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2025-05-23
DOI
https://doi.org/10.1109/lra.2025.3572826
Citations
3
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
3.83
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article

Safety-Aware UAV Formation Scheme for Guiding UGVs Through Obstacle-Laden Environments

Sheng Quan Xie, Yuanlong Xie, Youmin Zhang, Shuting Wang et al.
3 citations
IEEE Robotics and Automation Letters
Robotic Path Planning Algorithms
3.83
article

Safety-Aware UAV Formation Scheme for Guiding UGVs Through Obstacle-Laden Environments

Sheng Quan Xie, Yuanlong Xie, Youmin Zhang, Shuting Wang, Ruikang Xiao
article en
3 citations

Abstract

Using unmanned aerial vehicle (UAV) formations to guide unmanned ground vehicles (UGVs) through unstructured obstacle-laden areas leads to highly efficient execution of tasks such as the transportation of supplies. However, existing methods fail to efficiently plan obstacle-avoidance strategies for the entire UAV-UGV swarm. Additionally, the formation controller and planner are isolated, resulting in the degradation of formation tracking accuracy, which presents potential security risks. This paper proposes a novel UAV formation scheme that integrates safe corridor (SC) generation, trajectory fitting, and formation tracking to ensure operational safety. The scheme employs a novel line-of-sight (LOS) mechanism to optimize A*-planned waypoints, generating the SC as an obstacle-avoidance strategy. A minimum snap trajectory is fitted to the optimized waypoints with SC constraints. Bridged by the trajectory, the scheme develops a rigid-graph-based controller (RGC) to track the planning result, enabling dynamic formation maneuvering within the SC. Consequently, the proposed UAV formation scheme achieves obstacle-avoidance guidance by restricting the UGVs to the formation projection. The validation results demonstrate that the proposed scheme exhibits enhanced robustness and superior planning capabilities compared to traditional methods.

IEEE Robotics and Automation LettersVol. 10(7)
University of Leeds (GB), Huazhong University of Science and Technology (CN), Concordia University (CA)
Openalex Percentile: Top 7%
Robotic Path Planning Algorithms
3.83
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Safety-Aware UAV Formation Scheme for Guiding UGVs Through Obstacle-Laden Environments — Sheng Quan Xie, Yuanlong Xie, et al. · IEEE Robotics and Automation Letters (2025) | TGRS Research Map | TGRS