TreeLoc: 6-DoF LiDAR Global Localization in Forests via Inter-Tree Geometric Matching

• URL: http://arxiv.org/abs/2602.01501v2
• Date: Tue, 03 Feb 2026 08:23:36 GMT
• Title: TreeLoc: 6-DoF LiDAR Global Localization in Forests via Inter-Tree Geometric Matching
• Abstract summary: We propose TreeLoc, a LiDAR-based global localization framework for forests.<n>On diverse forest benchmarks, TreeLoc outperforms baselines, achieving precise localization.<n>We also propose applications for long-term forest management using descriptors from a compact global tree database.
• Score: 7.581546372433995
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Reliable localization is crucial for navigation in forests, where GPS is often degraded and LiDAR measurements are repetitive, occluded, and structurally complex. These conditions weaken the assumptions of traditional urban-centric localization methods, which assume that consistent features arise from unique structural patterns, necessitating forest-centric solutions to achieve robustness in these environments. To address these challenges, we propose TreeLoc, a LiDAR-based global localization framework for forests that handles place recognition and 6-DoF pose estimation. We represent scenes using tree stems and their Diameter at Breast Height (DBH), which are aligned to a common reference frame via their axes and summarized using the tree distribution histogram (TDH) for coarse matching, followed by fine matching with a 2D triangle descriptor. Finally, pose estimation is achieved through a two-step geometric verification. On diverse forest benchmarks, TreeLoc outperforms baselines, achieving precise localization. Ablation studies validate the contribution of each component. We also propose applications for long-term forest management using descriptors from a compact global tree database. TreeLoc is open-sourced for the robotics community at https://github.com/minwoo0611/TreeLoc.

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