A Swarm Formation Control System for AAV-Enabled Internet of Things With Hybrid Path Planning

To address the problem of real-time path planning for autonomous aerial vehicle (AAV) formations in complex environments, this article proposes a hybrid path planning control system tailored for AAV-enabled Internet of Things (IoT) utilizing near-field communication (NFC) among them. We model the AAV formation problem as an undirected graph, and first design a virtual leader-follower method based on the consistency principle of distributed systems. After that, we present an innovative hybrid path planning method (named ASAP-A*), combining A* and artificial potential field methods. It effectively reduces redundant points in the path and optimizes the AAV trajectory by B-spline smoothing to meet AAV trajectory requirements. Finally, we construct a user-friendly AAV swarms formation control system based the proposed methods, tackling the complexity of operating existing systems, and verifying the effectiveness of our solutions.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-12-30
DOI
https://doi.org/10.1109/jiot.2024.3523586
Citations
1
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
1.30

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article

A Swarm Formation Control System for AAV-Enabled Internet of Things With Hybrid Path Planning

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IEEE Internet of Things Journal
UAV Applications and Optimization
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article

A Swarm Formation Control System for AAV-Enabled Internet of Things With Hybrid Path Planning

Zhaolong Ning, Lei Xiao, Zhihao Mu, He Liu, Xiaojie Wang, Xiaoying Zhang, Jiawei Zhang
article en
1 citations

Abstract

To address the problem of real-time path planning for autonomous aerial vehicle (AAV) formations in complex environments, this article proposes a hybrid path planning control system tailored for AAV-enabled Internet of Things (IoT) utilizing near-field communication (NFC) among them. We model the AAV formation problem as an undirected graph, and first design a virtual leader-follower method based on the consistency principle of distributed systems. After that, we present an innovative hybrid path planning method (named ASAP-A*), combining A* and artificial potential field methods. It effectively reduces redundant points in the path and optimizes the AAV trajectory by B-spline smoothing to meet AAV trajectory requirements. Finally, we construct a user-friendly AAV swarms formation control system based the proposed methods, tackling the complexity of operating existing systems, and verifying the effectiveness of our solutions.

IEEE Internet of Things JournalVol. 12(12)
Chongqing University of Posts and Telecommunications (CN), National University of Defense Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 11%
UAV Applications and Optimization
1.30
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