A FAST KNOWLEDGE-BASED PLANE RECONSTRUCTION METHOD FROM NOISY 3D POINT CLOUD DATA

摘要

This paper presents a knowledge-based method of planar surface reconstruction from noisy 3D point cloud data which produces a fast and reliable modelling of an indoor environment. The data used is obtained from a laser scanner, which is known for its rapidness and accuracy in 3D reconstruction. The laser is attached together with a servo motor at a 45cm height mobile platform to give a complete 180 from top to bottom, and 180 from left to right, which allows the reconstruction process to be made on just a single scan. It takes about 1.3 seconds for the algorithm to process and produce the 3D modelling of all existing surfaces on a normal working computer. Our method has been tested in both uncluttered and real office environment. It can be applied towards developing an asbuilt building information models (BIM) in architectural and semantic mapping for robotics applications.