华中师范大学学报（自然科学版）2017，Vol.51Issue(2)：264-272,9.
基于改进ICP算法的室内环境三维地图创建研究
Reconstructing 3D map in indoor environment based on an improved ICP algorithm
摘要
Abstract
In this paper,an improved Iterative Closest Point (ICP) algorithm is proposed based on features with the discrete selection mechanism for motion estimation to reconstruct 3D map in indoor environment.Firstly,SURF features in consecutive RGB images are extracted and matched.Then,Random Sample Consensus (RANSAC) algorithm is used for initial registration to optimize the initial pose of features and remove the outliers.Furthermore,secondary registration is applied to calculate the refined transformation between point-clouds in the different coordinate systems combining with the Iterative Closest Point algorithm which based on features with the discrete selection mechanism.Finally,the trajectory of the moving camera is optimized using General Gragh Optimization (g2o) framework combining with key frames,and 3D map is reconstructed through projecting 3D points cloud observed by the camera into global map according to current camera poses.The performance of our proposed algorithm in five public datasets is tested.The results demonstrate that the algorithm is feasible and effectively with the translational error just of 0.059m and ability to generate the 3D map of environment accurately.关键词
离散选取机制/改进特征点ICP算法/RANSAC/g2o/关键帧Key words
discrete selection mechanism/improved ICP algorithm/RANSAC/g2o/key frames分类
天文与地球科学引用本文复制引用
张彦铎,袁博,李迅..基于改进ICP算法的室内环境三维地图创建研究[J].华中师范大学学报（自然科学版）,2017,51(2):264-272,9.基金项目
国家863计划项目(2013AA12A202) （2013AA12A202）
国家自然科学基金项目(41501505). （41501505）
