Whitepapers

Comparison of the Trimble MX9 and the Trimble MX50 mobile mapping systems 15 Conclusions The results of the comparative analysis we carried out for each type of considered technology helps in the definition of which mobile mapping system better fits specific applications. Different types of users require different sensors and sensor usage. Therefore, an understanding of use cases is crucial in guiding customer decisions versus one or another mobile mapping solution. Navigation sensors As demonstrated by tests described in the section, Test results and conclusions on page 6, the MX9 FOG IMU technology provides better positioning performances when in difficult GNSS conditions. In such scenarios, the MX9 system demonstrates better performances when positioning drift occurs. Still the adoption of GCPs might be needed, according to the specific application requirements. However, in the same degraded GNSS conditions, the number and distance between used GCPs would be minor if compared when using the MX50 system. That's why for survey-grade applications in difficult GNSS scenarios, using a MX9 system might result in a minor effort for the creation of a GCP network when required, and in general, a more robust control of the drift in the absolute positioning. When the secondary GNSS antenna (GAMS) is not used, FOG IMU technology proved to provide a quicker heading initialization compared to the MEMS IMU of the MX50 (AP20). The effect of this enables easier field operation and higher flexibility. Cameras Both systems have the same 360° spherical camera. This camera is the ideal solution for data navigation and for colorization of point clouds with RGB values. As illustrated by the camera specifications and by the section Comparing the imaging sensors on page 7, Trimble MX9 oblique cameras are equipped with different optic components enabling a better resolution in the collected images, when compared to the standard 360° camera. The resulting higher GSD resolution enables oblique camera usage for visual inspection tasks, or in applications where being able to detect small details are important. The MX9 back-down looking camera, for example, gives the option to identify, position and measure road defects that would otherwise not be visible from the spherical camera. Similarly, the two MX9 lateral oblique cameras can be oriented in the most efficient way to collect small details of features that otherwise would require additional operator visits. Potentially, the MX50 system could use an external dedicated camera (the same applies to the MX9 system), but it requires additional hardware and calibration procedures. Laser Different elements have been considered when comparing the two systems. In general, the most evident element on screen is the density. Having the option to be two times faster in both generating pulses and in spinning the laser, at equal driving speed, the MX9 system produces a denser point cloud that is useful in applications where 3D details are necessary. In addition, these features give the MX9 system the ability to have a very good point distribution and density even at higher speed, which could be crucial, for example, in rail applications and in highway mapping. The MX50 system could achieve similar results but this would require a slower speed during the data collection operations. The higher PRR of the MX9 system enables data collection on power lines, facilitating tasks like overhead cable extraction and vertical clearance measurements. The MX9 PRR enables good point distribution (on same scan lines) even at the possible long-range measurements. Large corridors and high building facades remain well defined. MX9 multiple laser returns can enable getting details from objects or features even partially masked by other elements like bushes, trees and fences. The MX9 multiple laser returns provide sufficient information of objects partially covered or hidden. This is also beneficial in dusty conditions, for example, mines, where different laser beams might hit particles, thus not being able to get echo returns of beneath features.

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