Development and Initial Assessment of a Low Cost Mobile Mapping System

Author(s):  
Andrea Masiero ◽  
Francesca Fissore ◽  
Alberto Guarnieri ◽  
Antonio Vettore ◽  
Ugo Coppa
2010 ◽  
Vol 65 (6) ◽  
pp. 514-522 ◽  
Author(s):  
Anttoni Jaakkola ◽  
Juha Hyyppä ◽  
Antero Kukko ◽  
Xiaowei Yu ◽  
Harri Kaartinen ◽  
...  

Author(s):  
E. Frentzos ◽  
E. Tournas ◽  
D. Skarlatos

Abstract. The aim of this study is to develop a low-cost mobile mapping system (MMS) with the integration of vehicle-based navigation data and stereo images acquired along vehicle paths. The system consists of a dual frequency GNSS board combined with a low-cost INS unit and two machine vision cameras that collect colour image data for road and roadside objects. The navigation data and the image acquisition are properly synchronized to associate position and attitude to each digital frame captured. In this way, upon pixel location of objects appearing on the video frames, their absolute geographical coordinates can be extracted by employing standard photogrammetric methods. Several calibration steps are implemented before survey operation: camera calibration, relative orientation between cameras and determination of rotation angles and offsets between vehicle and cameras reference frames. A software tool has been developed to facilitate and speed up the calibration procedures. Furthermore, easy object coordinate extraction is supported, either in auto mode, where the conjugate image coordinates are obtained in real time using image correlation techniques. Several surveying experiments were executed to certify and check the accuracy and efficiency of the system. From the achieved results, the developed system is efficient for collecting and positioning road spatial objects such as such as road boundaries, traffic lights, road signs, power poles, etc, more rapidly and less expensively. The obtained absolute positional accuracy is less than 1 meter, depending on the availability and quality of the GPS signal.


Sensors ◽  
2012 ◽  
Vol 12 (3) ◽  
pp. 2935-2953 ◽  
Author(s):  
Sergio Madeira ◽  
José A. Gonçalves ◽  
Luísa Bastos

2003 ◽  
Vol 18 (101) ◽  
pp. 5-26 ◽  
Author(s):  
João Fernando C. Da Silva ◽  
Paulo de Oliveira Camargo ◽  
Rodrigo B. A. Gallis

Author(s):  
A. Nüchter ◽  
D. Borrmann ◽  
P. Koch ◽  
M. Kühn ◽  
S. May

Mobile mapping systems are commonly mounted on cars, ships and robots. The data is directly geo-referenced using GPS data and expensive IMU (inertial measurement systems). Driven by the need for flexible, indoor mapping systems we present an inexpensive mobile mapping solution that can be mounted on a backpack. It combines a horizontally mounted 2D profiler with a constantly spinning 3D laser scanner. The initial system featuring a low-cost MEMS IMU was revealed and demonstrated at <i>MoLaS: Technology Workshop Mobile Laser Scanning at Fraunhofer IPM</i> in Freiburg in November 2014. In this paper, we present an IMU-free solution.


Author(s):  
G. J. Tsai ◽  
K. W. Chiang ◽  
C. H. Chu ◽  
Y. L. Chen ◽  
N. El-Sheimy ◽  
...  

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.


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