期刊文献+

基于RGB-D传感器的3D室内环境地图实时创建 被引量:6

RGB-D sensor based real-time 3Dmap building for indoor environment
在线阅读 下载PDF
导出
摘要 对基于RGB-D传感器的室内环境3D地图的建立方法进行研究,针对最流行的RGBD-SLAM算法在建立完整3D地图时遇到的问题,提出了两个方面改进。一是改进子地图划分标准,使得多层图抽象可以更好的反映环境的拓扑结构,并具有更高的效率;二是在地图输出模块中添加冗余点去除模块,使得最后得到的地图数据量减少,为后续操作提供更准确的数据。实验中,将改进的方法和原始方法进行比较,比较结果表明,两个改进在建立室内3D地图时是完全有效的。 The building method of the indoor 3D environment using the RGB-D sensor is researched, and the problem of using fa mous RGBD-SLAM algorithm to build a complete 3D map is analyzed, and then two improvements are proposed. First, the sub map dividing method is advanced, which makes the multi-graph abstraction better reflect the topology of the environment, and become more efficient. Second, a redundant point removing module in the map output module is added, which can reduce the re sulting map data and provide more accurate data for the follow-up operations. In the experiment, the improved method is com pared with the original one, and the results demonstrate the establishment of two improvements for indoor 3D map building is completely valid.
出处 《计算机工程与设计》 CSCD 北大核心 2014年第1期203-207,共5页 Computer Engineering and Design
基金 国际热核聚变实验堆(ITER)计划专项基金项目(2011GB113005)
关键词 RG&D传感器 3D同步定位与地图创建 多层图优化 点云融合 冗余点去除 RGB-D sensor 3D SLAM multi-level submap point cloud merging redundant points reduction
  • 相关文献

参考文献10

  • 1Peter H,Michael K,Evan H. RGB-D mapping:Using depth cameras for dense 3D modeling of indoor environments[A].2010.
  • 2Grisetti G,Slawornir G,Cyrill S. Efficient estimation of accurate rnaximum likelihood maps in 3D[A].2007.
  • 3Giorgio G,Cyrill S,Wolfram B. Non-linear connstraint network optimization for efficient map learning[J].IEEE Trannsactions on Intelligent Transportation Systems,2009,(3):428-439.
  • 4Durrant-Whyte H,Bailey T. Simultaneous localization and mapping (SLAM):Part Ⅰ the essential algorithms[J].Robotics and Automation Magazine,2009,(2):99-110.
  • 5Fioraio N,Konolige K. Realtime visual and point cloud SLAM[A].2011.
  • 6Ni K,Dellaert F. Multi-level submap based SLAM using nested dissection[A].2010.2558-2565.
  • 7Biswas J,Veloso M. Depth camera based localization and navigation for indoor mobile robots[A].2011.
  • 8Engelhard N,FelixEndres,UrgenHess J. Real-time 3D visual SLAM with a hand-held RGB-D camera[A].2010.
  • 9Herrera C,Daniel K,Heikkil(a) J. Depth and color camera calibration with distortion correction[J].{H}IEEE Transactions on Pattern Analysis and Machine Intelligence,2012,(10):2058-2064.
  • 10Cui Y,Sehuon S,Thrun S. Algorithms for 3D shape scanning with a depth camera[A].2012.

同被引文献61

  • 1闫友彪,陈元琰.机器学习的主要策略综述[J].计算机应用研究,2004,21(7):4-10. 被引量:57
  • 2郑宏,王景川,陈卫东.基于地图的移动机器人自定位与导航系统[J].机器人,2007,29(4):397-402. 被引量:23
  • 3Newcombe R A, Davison A J, Izadi S, et al. KinectFusion:real-time dense surface mapping and tracking[C] //Proc of the 10th IEEE International Symposium on Mixed and Augmented Reality. [S. l.] :IEEE Press, 2011:127-136.
  • 4Henry P, Krainin M, Herbst E, et al. RGB-D mapping:using depth cameras for dense 3D modeling of indoor environments[C] //Proc of the 12th International Symposium on Experimental Robotics. Berlin:Springer, 2014:477-491.
  • 5Huang A S, Bachrach A, Henry P, et al. Visual odometry and mapping for autonomous flight using an RGB-D camera[C] //Proc of International Symposium on Robotics Research. 2011:1-16.
  • 6Kerl C, Sturm J, Cremers D. Dense visual SLAM for RGB-D cameras[C] //Proc of IEEE/RSJ International Conference on Intelligent Robots and Systems. [S. l.] :IEEE Press, 2013:2100-2106.
  • 7Wikipedia. Kinect[EB/OL] . http://en. wikipedia. org/wiki/kinect.
  • 8Kerl C, Sturm J, Cremers D. Robust odometry estimation for RGB-D cameras[C] //Proc of IEEE International Conference on Robotics and Automation. [S. l.] :IEEE Press, 2013:3748-3754.
  • 9Whelan T, Johannsson H, Kaess M, et al. Robust real-time visual odometry for dense RGB-D mapping[C] //Proc of IEEE International Conference on Robotics and Automation. [S. l.] :IEEE Press, 2013:5724-5731.
  • 10Bay H, Ess A, Tuytelaars T, et al. SURF:speeded up robust features[J] . Computer Vision and Image Understanding, 2008, 110(3):346-359.

引证文献6

二级引证文献25

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部