Hierarchical Formation Control of Model-Unknown Multi-USV Based on LOS Tracking and Consensus

This paper proposes a model-free hierarchical control approach for multi-USV formation, aiming to enhance adaptability and convergence speed. The upper layer utilizes a consensus protocol for trajectory planning, while the lower layer incorporates an improved Line-of-Sight tracking algorithm for path following. A trajectory prediction method is integrated to enable realtime, dynamic strategy adaptation to changing environmental conditions. The proposed method accelerates convergence by bypassing the LOS controller at later stages, ensuring efficient, collision-free formation control. Experimental results validate the robustness, flexibility, and efficacy of the approach in heterogeneous and dynamic multi-USV environments.

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Publication Details

Published
2025-05-17
DOI
https://doi.org/10.1109/yac66630.2025.11150039
Primary Topic
Healthcare Decision-Making and Restraints
Type
article
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article

Hierarchical Formation Control of Model-Unknown Multi-USV Based on LOS Tracking and Consensus

Healthcare Decision-Making and Restraints
article

Hierarchical Formation Control of Model-Unknown Multi-USV Based on LOS Tracking and Consensus

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Abstract

This paper proposes a model-free hierarchical control approach for multi-USV formation, aiming to enhance adaptability and convergence speed. The upper layer utilizes a consensus protocol for trajectory planning, while the lower layer incorporates an improved Line-of-Sight tracking algorithm for path following. A trajectory prediction method is integrated to enable realtime, dynamic strategy adaptation to changing environmental conditions. The proposed method accelerates convergence by bypassing the LOS controller at later stages, ensuring efficient, collision-free formation control. Experimental results validate the robustness, flexibility, and efficacy of the approach in heterogeneous and dynamic multi-USV environments.

Southeast University (CN)
Climate action
Openalex Percentile: Top 38%
Healthcare Decision-Making and Restraints
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