부산대학교 도서관

A point cloud is a data set including a number of 3-dimensional point data. Mobile robots such as autonomous vehicles require point clouds for localization, which is a technique for estimating self-position. Localization is a kind of similarity searches between the current point cloud from on-board sensors and historical point clouds observed in advance. Thus, how to manage historical point clouds is quite important. But, some experimental systems for mobile robots do not care about data management of historical point clouds. They are usually stored in text files and are fully loaded on memory at the time of startup. We believe that historical point clouds should be managed by DBMS and loaded by queries if need arises. Before challenging this research theme, in this paper, we investigate performance of querying point clouds stored in RDBMS (PostgreSQL and PostGIS). We measure execution time for range query and rectangular query, and performance of B-tree index and R-tree index.