STAG: A Sparse Traversability-Aware Graph Representation from Grid-Based Costmaps for Robotic Navigation
The STAG method converts dense grid-based maps into a compact, sparse graph for faster global path planning. It achieves this by creating a backbone of free space boundaries and adding specialized nodes to summarize homogeneous terrain areas and capture sharp changes in traversability. This results in significantly reduced planning time and memory while maintaining good path quality for large maps.