BEVPlace: Learning LiDAR-based Place Recognition using Bird's Eye View Images

Understand

Place recognition is a key module for long-term SLAM systems.

• Current LiDAR-based place recognition methods usually use representations of point clouds such as unordered points or range images.
• These methods achieve high recall rates of retrieval, but their performance may degrade in the case of view variation or scene changes.
• In this work, we explore the potential of a different representation in place recognition, i.e.