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
Language-EXtended Indoor SLAM (LEXIS): A Versatile System for Real-time Visual Scene Understanding
Christina Kassab, Matias Mattamala, Lintong Zhang, Maurice Fallon
HeLiPR: Heterogeneous LiDAR Dataset for inter-LiDAR Place Recognition under Spatiotemporal Variations
Minwoo Jung, Wooseong Yang, Dongjae Lee, Hyeonjae Gil, Giseop Kim, Ayoung Kim