R2SCAT-LPR: Rotation-Robust Network with Self- and Cross-Attention Transformers for LiDAR-Based Place Recognition

R2SCAT-LPR: Rotation-Robust Network with Self- and Cross-Attention Transformers for LiDAR-Based Place Recognition

LiDAR-based place recognition (LPR) is crucial for the navigation and localization of autonomous vehicles and mobile robots in large-scale outdoor environments and plays a critical role in loop closure detection for simultaneous localization and mapping (SLAM). Existing LPR methods, which utilize 2D...

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Bibliographic Details
Main Authors: Weizhong Jiang, Hanzhang Xue, Shubin Si, Liang Xiao, Dawei Zhao, Qi Zhu, Yiming Nie, Bin Dai
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Remote Sensing
Subjects:
LiDAR-based place recognition
self-attention
cross-attention
multi-level patch features
global context
rotation-robust
Online Access:https://www.mdpi.com/2072-4292/17/6/1057
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