A Multi-Source, Multi-Temporal, Multi-Modal Crowdsourced Map Matching and Alignment Method Based on Pose-Graph Optimization [Patent]

This invention provides a method for matching and aligning multi-modal, multi-temporal vehicle-side mapping data. Based on pose-graph optimization, it maximally eliminates the global-position inconsistencies among local maps uploaded by different vehicles at different times, thereby producing a more tightly converged map form. This reduces the difficulty of the subsequent map-fusion stage and enables computation of a cloud-side crowdsourced fused map under more globally consistent poses.

Download paper here