CODE: Complete Coverage AAV Exploration Planner Using Dual-Type Viewpoints for Multi-Layer Complex Environments

We present an autonomous exploration method for autonomous aerial vehicles (AAVs) for three-dimensional (3D) exploration tasks. Our approach, utilizing a cooperation strategy between common viewpoints and frontier viewpoints, fully leverages the agility and flexibility of AAVs, demonstrating faster and more comprehensive exploration than the current state-of-the-art. Common viewpoints, specifically designed for AAVs exploration, are evenly distributed throughout the 3D space for 3D exploration tasks. Frontier viewpoints are positioned at the centroids of clusters of frontier points to help the AAV maintain motivation to explore unknown complex 3D environments and navigate through narrow corners and passages. This strategy allows the AAV to access every corner of the 3D environment. Additionally, our method includes a refined relocation mechanism for AAVs specifically. Experimental comparisons show that our method ensures complete exploration coverage in environments with complex terrain. Our method outperforms TARE DSVP, GBP and MBP by the coverage rate of 64%, 63%, 54% and 49% respectively in garage-D. In narrow tunnels, ours and DSVP are the only two evaluated methods that achieve complete coverage, with ours outperforming DSVP by 35% in exploration efficiency.

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Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2024-12-23
DOI
https://doi.org/10.1109/lra.2024.3521179
Citations
2
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.50
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article

CODE: Complete Coverage AAV Exploration Planner Using Dual-Type Viewpoints for Multi-Layer Complex Environments

Ruijiao Li, Tian Lan, Heyuan Zhu, Xuan Zhao et al.
2 citations
IEEE Robotics and Automation Letters
Robotic Path Planning Algorithms
0.50
article

CODE: Complete Coverage AAV Exploration Planner Using Dual-Type Viewpoints for Multi-Layer Complex Environments

Ruijiao Li, Tian Lan, Heyuan Zhu, Xuan Zhao, S. MA, Huiliang Shang
article en
2 citations

Abstract

We present an autonomous exploration method for autonomous aerial vehicles (AAVs) for three-dimensional (3D) exploration tasks. Our approach, utilizing a cooperation strategy between common viewpoints and frontier viewpoints, fully leverages the agility and flexibility of AAVs, demonstrating faster and more comprehensive exploration than the current state-of-the-art. Common viewpoints, specifically designed for AAVs exploration, are evenly distributed throughout the 3D space for 3D exploration tasks. Frontier viewpoints are positioned at the centroids of clusters of frontier points to help the AAV maintain motivation to explore unknown complex 3D environments and navigate through narrow corners and passages. This strategy allows the AAV to access every corner of the 3D environment. Additionally, our method includes a refined relocation mechanism for AAVs specifically. Experimental comparisons show that our method ensures complete exploration coverage in environments with complex terrain. Our method outperforms TARE DSVP, GBP and MBP by the coverage rate of 64%, 63%, 54% and 49% respectively in garage-D. In narrow tunnels, ours and DSVP are the only two evaluated methods that achieve complete coverage, with ours outperforming DSVP by 35% in exploration efficiency.

IEEE Robotics and Automation LettersVol. 10(2)
Fudan University (CN), Yiwu Science and Technology Research Institute (CN)
Openalex Percentile: Top 32%
Robotic Path Planning Algorithms
0.50
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CODE: Complete Coverage AAV Exploration Planner Using Dual-Type Viewpoints for Multi-Layer Complex Environments — Ruijiao Li, Tian Lan, et al. · IEEE Robotics and Automation Letters (2024) | TGRS Research Map | TGRS