## 3 Experiment Description
### Experiment Details  
The goal of this experiment was to evaluate the accuracy of the kinematic point-cloud collected from different sensors using the proposed ICP-based accuracy assessment method. Six kinematic point cloud datasets of the test facility acquired with different navigation sensors were evaluated against the static point cloud. The full area static and kinematic point clouds are shown in Figure 3. \begin{table}
\begin{tabular}{c c c c} \hline  & \(\Delta\leq 0.015\) m & \(0.015\) m \(\leq\Delta\leq 0.025\) m & \(\Delta\geq 0.025\) m \\ \hline
**Accuracy** & & & \\ Horizontal & 87.50\% & 10.60\% & 1.90\% \\ Vertical & 100.00\% & 0.00\% & 0.00\% \\
**Precision** & & & \\ Horizontal & 78.30\% & 17.40\% & 4.30\% \\ Vertical & 98.10\% & 1.90\% & 0.00\% \\ \hline \end{tabular}
\end{table} 
Table 1: Accuracy and precision analysis of the static, reference point cloud. Percentages indicate the proportion of coordinate differences lying within each indicated range. Figure 2: Top view of the study area (image from Google Maps). The dotted red line indicates the extents of the static laser scanner data. The MMS comprises a Velodyne VLP-16 (Velodyne Lidar, San Jose, CA, USA) deployed in tandem with a NovAtel SPAN system (Novatel Inc., Calgary, AB, Canada), a tightly coupled GNSS/IMU system that includes a multi-frequency, multi-constellation receiver  
Figure 3: Static and kinematic point clouds of the entire study area: (**a**) Static point cloud (the test facility); (**b**) Sample kinematic point cloud—loop A; (**c**) Sample kinematic point cloud—loop B.  
and an IMU. The Velodyne VLP-16 sensor comprises a vertical array of 16 lasers with an angular spacing such that the field-of-view is approximately 30\({}^{\circ}\). Continuous rotation of the laser array about the sensor's vertical axis allows collection of a panoramic point cloud. The system was fitted with three different IMUs for testing: an InvenSense IAM20680 (InvenSense Inc., City San Jose, CA, USA); an Epson G320N (Seiko Epson Corporation, Nagano, Japan); and a Honeywell HG4930 AN01 (SPAN-CPT7; Honeywell International Inc., Charlotte, NC, USA). The InvenSense falls into the consumer MEMS (<$100) category while the other IMUs are commercial MEMS (>$100). The datasets were captured with three different test setups on 21 March, 29 October, and 31 October 2019. Figure 4 shows an example of the instrumentation setup. For the first data collection, the Invensens was mounted on the same base plate as the VLP-16 and the Epson was on a different plate but along the same beam. The second and third data collections included both the Honeywell and Epson on the same base plate as the VLP-16. The weather conditions were all similar for the three data collections, no rain or snow was present. For each dataset, a reference trajectory was determined using a Honeywell LASEREF V Micro Inertial Reference System (\(\mu\)IRS; Honeywell International Inc., Charlotte, NC, USA). This navigation-grade IMU provides high-accuracy trajectory data to allow quantification of MMS georeferencing accuracy independent of the Velodyne. The proposed methodology was applied on the six kinematic data clouds one at a time. Different time intervals were tested to quantify the impact of temporal slice length on the accuracy assessment results. Each cloud was sliced based on 5 s and 10 s time interval lengths. An example of kinematic point cloud slicing with 5 s time interval is shown in Figure 5. Areas with no overlap with the static cloud have been excluded from testing. In some locations, the ICP did not converge. These slices were excluded from the analysis as they did not have strong point geometry due to excessive clutter and areas with insufficiently geometric features to allow registration of the point clouds. For this project, the registration results were inspected visually to ensure proper alignment between the kinematic and the static data.