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
An Evaluation and Ranking of Different Voting Schemes for Improved Visual Place Recognition
Maria Waheed, Michael Milford, Xiaojun Zhai, Klaus McDonald-Maier, Shoaib Ehsan
ColonMapper: topological mapping and localization for colonoscopy
Javier Morlana, Juan D. Tardós, J. M. M. Montiel
Patch-DrosoNet: Classifying Image Partitions With Fly-Inspired Models For Lightweight Visual Place Recognition
Bruno Arcanjo, Bruno Ferrarini, Michael Milford, Klaus D. McDonald-Maier, Shoaib Ehsan