# A Fast Point Clouds Registration Algorithm Based on ISS-USC Feature for the 3D Laser Scanner
## 4 Experimental Results and Analysis
### Experimental Procedure
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Model**} & **Voxel Filter+ 3 DSC +** & **Improved Voxel Filter +** & **Voxel Filter+ USC +** & **Proposed Algorithm** \\  & **RANSAC + ICP** & **3 DSC + RANSAC + ICP** & **RANSAC + ICP** & \\ \hline Bunny & 6.69635 \(\times\) 10\({}^{-5}\) & 6.69635 \(\times\) 10\({}^{-5}\) & 6.69635 \(\times\) 10\({}^{-5}\) & 6.69635 \(\times\) 10\({}^{-5}\) \\ ArmAdillo & 4.06044 \(\times\) 10\({}^{-5}\) & 4.67503 \(\times\) 10\({}^{-5}\) & 4.06102 \(\times\) 10\({}^{-5}\) & 4.67117 \(\times\) 10\({}^{-5}\) \\ Dragon & 0.00233421 & 0.00229143 & 0.80076627 & 0.00228654 \\ Drill & 4.84577 \(\times\) 10\({}^{-6}\) & 4.68711 \(\times\) 10\({}^{-6}\) & 4.81674 \(\times\) 10\({}^{-6}\) & 4.71003 \(\times\) 10\({}^{-6}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Registration error for four models of each algorithm/m. registration effect of the Dragon point clouds is wrong. However, the proposed algorithm can accurately register using the improved voxel filter under the USC feature descriptor, which shows that the improved voxel filter can improve the registration accuracy. Figure 13 shows the original image of the Dragon point clouds registration and the result under the proposed algorithm. For the Drill point clouds data, the data is relatively simple, so there is little difference in time and registration accuracy. The registration time of the proposed algorithm is the shortest and the registration accuracy is relatively high. Whether it is 3 DSC feature descriptor or USC descriptor, the registration time is reduced, and the registration accuracy is improved after using the improved voxel filter. Figure 14 shows the registration results of four models under the proposed algorithm. The source point clouds, the target point clouds, and the registered point clouds are displayed in one figure. The source point clouds are set to green, the target point clouds are set to blue, and the registered point clouds are set to red. It can be seen that the blue point clouds and the red point clouds almost overlap, indicating that the proposed algorithm has high registration accuracy. Figure 12: Registration results of the USC + RANSAC + ICP algorithm without the improved voxel filter for the Dragon model. (**a**) Dragon original image. (**b**) Registration result image. Figure 13: Registration results of the proposed algorithm for the Dragon model. (**a**) Dragon original image. (**b**) Registration result image. In order to further verify the feasibility of the proposed algorithm, the registration experiment of the VGA connector for monitor is carried out. First, a single VGA connector point clouds are obtained as the template point clouds, and then different scene point clouds are obtained as the target point clouds. The template point clouds are used as the source point clouds and the target scene point clouds for registration. The final registration pose information can be sent to the robot for decision-making. Point clouds from two different scenes are collected, and the obtained point clouds of the two scenes are shown in Figure 15.  
Figure 14: Registration results of the proposed algorithm with four models. (**a**) Bunny registration result. (**b**) Armadillo registration result. (**c**) Dragon registration result. (**d**) Drill registration result. The background of the collected scene point clouds are removed and the improved voxel filter is used to remove outliers. Table 6 shows the number of filtered points and extracted ISS feature points for the two scenes under different grid sizes. The grid size is selected by experiment to be 0.8 m. Figure 16 is the feature points plot extracted from two scenes. An experiment is set up to register the VGA connector for monitor. Figure 17 is the operation diagram of the experimental site. Figure 18 is the registration result diagram under the two scenes. The template point clouds are set to green, the target scene point clouds are set to blue, and the registered point clouds are set to red.