Place Recognition
Place recognition, a crucial component of autonomous systems, aims to identify previously visited locations using sensor data. Current research emphasizes robust and efficient methods across diverse sensor modalities (cameras, LiDAR, radar), focusing on model architectures like transformers, convolutional neural networks, and novel feature aggregation techniques to handle variations in viewpoint, lighting, and environmental changes. These advancements are vital for improving the reliability and scalability of robotics, autonomous driving, and mapping applications, particularly in challenging, GPS-denied environments.
Papers
VXP: Voxel-Cross-Pixel Large-scale Image-LiDAR Place Recognition
Yun-Jin Li, Mariia Gladkova, Yan Xia, Rui Wang, Daniel Cremers
Evaluation and Deployment of LiDAR-based Place Recognition in Dense Forests
Haedam Oh, Nived Chebrolu, Matias Mattamala, Leonard Freißmuth, Maurice Fallon
ReFeree: Radar-based efficient global descriptor using a Feature and Free space for Place Recognition
Byunghee Choi, Hogyun Kim, Younggun Cho