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This repository provides implementation of an incremental k-d tree for robotic applications.
LiLi-OM is a tightly-coupled, keyframe-based LiDAR-inertial odometry and mapping system for both solid-state-LiDAR and conventional LiDARs.
Robust LiDAR SLAM with a versatile plug-and-play loop closing and pose-graph optimization.
[CVPR2023] DeepMapping2: Self-Supervised Large-Scale LiDAR Map Optimization
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Updated
Oct 7, 2023
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Python
Make it Dense: Self-Supervised Geometric Scan Completion of Sparse 3D LiDAR Scans in Large Outdoor Environments
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Dec 7, 2023
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Python
This is the official repository of LiLi-OM, a tightly-coupled, keyframe-based LiDAR-inertial odometry and mapping system for both solid-state-LiDAR and conventional LiDARs.
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Updated
Feb 25, 2024
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