The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XL-1/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W4, 183–188, 2015
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W4, 183–188, 2015

  26 Aug 2015

26 Aug 2015


G. J. Tsai1, K. W. Chiang1, C. H. Chu1, Y. L. Chen1, N. El-Sheimy2, and A. Habib3 G. J. Tsai et al.
  • 1Dept. of Geomatics Engineering, National Cheng-Kung University, No. 1, Daxue Road, East District, Tainan City, Taiwan
  • 2Dept. of Geomatics Engineering, The University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
  • 3Dept. of Civil Engineering, The University of Purdue, 610 Purdue Mall, West Lafayette, IN 47907, USA

Keywords: Mobile Mapping Systems, SLAM, Direct Georeferenced (DG), robot, indoor mapping, Position and Orientation System

Abstract. Over the years, Mobile Mapping Systems (MMSs) have been widely applied to urban mapping, path management and monitoring and cyber city, etc. The key concept of mobile mapping is based on positioning technology and photogrammetry. In order to achieve the integration, multi-sensor integrated mapping technology has clearly established. In recent years, the robotic technology has been rapidly developed. The other mapping technology that is on the basis of low-cost sensor has generally used in robotic system, it is known as the Simultaneous Localization and Mapping (SLAM). The objective of this study is developed a prototype of indoor MMS for mobile mapping applications, especially to reduce the costs and enhance the efficiency of data collection and validation of direct georeferenced (DG) performance. The proposed indoor MMS is composed of a tactical grade Inertial Measurement Unit (IMU), the Kinect RGB-D sensor and light detection, ranging (LIDAR) and robot. In summary, this paper designs the payload for indoor MMS to generate the floor plan. In first session, it concentrates on comparing the different positioning algorithms in the indoor environment. Next, the indoor plans are generated by two sensors, Kinect RGB-D sensor LIDAR on robot. Moreover, the generated floor plan will compare with the known plan for both validation and verification.