Building a dense surface map incrementally from semi-dense point cloud and RGB images

作     者：Qian-shan LI Rong XIONG Shoudong HUANG Yi-ming HUANG 

作者机构：State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou 310027 China Faculty of Engineering and Information Technology The University of Technology Sydney NSW 2007 Australia ZJU-UTS Joint Center on Robotics Zhejiang University Hangzhou 310027 China Department of Control Science and Engineering Zhejiang University Hangzhou 310027 China 

出 版 物：《Frontiers of Information Technology & Electronic Engineering》 (信息与电子工程前沿（英文版）)

年 卷 期：2015年第16卷第7期

页      面：594-606页

核心收录：

学科分类：081104[工学-模式识别与智能系统] 08[工学] 0811[工学-控制科学与工程] 

基　　金：Project supported by the National Natural Science Foundation of China (Nos. 61075078 and 61473258) 

主　　题：Bionic robot Robotic mapping Surface fusion 

摘      要：Building and using maps is a fundamental issue for bionic robots in field applications. A dense surface map, which offers rich visual and geometric information, is an ideal representation of the environment for indoor/outdoor localization, navigation, and recognition tasks of these robots. Since most bionic robots can use only small light-weight laser scanners and cameras to acquire semi-dense point cloud and RGB images, we propose a method to generate a consistent and dense surface map from this kind of semi-dense point cloud and RGB images. The method contains two main steps： （1） generate a dense surface for every single scan of point cloud and its corresponding image（s） and （2） incrementally fuse the dense surface of a new scan into the whole map. In step （1） edge-aware resampling is realized by segmenting the scan of a point cloud in advance and resampling each sub-cloud separately. Noine within the scan is reduced and a dense surface is generated. In step （2） the average surface is estimated probabilistically and the non-coincidence of different scans is eliminated. Experiments demonstrate that our method works well in both indoor and outdoor semi-structured environments where there are regularly shaped objects.