## 5 Experimental Design and Results Analysis
### Construction of Dense Point Cloud Map and OctoMap  
This paper conducted experiments to validate the efficacy and applicability of the proposed algorithm in dense mapping and OctoMap construction, utilizing six representative RGB-D sequences from the TUM dataset (fr1_xyz, fr2_xyz, fr1_desk, fr2_desk, fr3_long_office, and fr3_walk_rpy), with Table 3 detailing the parameters of the selected sequences. These datasets encompass several environmental categories, including dynamic settings, static scenes, and varying trajectory lengths and motion attributes. Building upon the conventional ORB-SLAM3 technique, dense point cloud maps and octree maps were developed. The performances of the dense point cloud maps and octree maps generated under various scenarios were meticulously assessed by examining essential variables, including the point cloud dispersion, scene geometric completeness, and storage efficiency. This paper investigated the performances of several map representation approaches by comparing their mapping results on the TUM dataset, as illustrated in Figures 13-18. The experimental results indicate that the proposed approach effectively produces high-quality environmental maps across various situations, exhibiting notable benefits in dense reconstruction and spatial representation. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Algorithm** & **Max/m** & **Mean/m** & **Median/m** & **Min/m** & **Rmse/m** & **Sse/m2** & **Std/m** \\ \hline ORB-SLAM3 & 0.027522 & 0.010691 & 0.009721 & 0.001821 & 0.011777 & 0.021496 & 0.004938 \\ Our & 0.018487 & 0.005951 & 0.005655 & 0.001261 & 0.006580 & 0.006278 & 0.002808 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Average absolute trajectory error. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Algorithm** & **Max/m** & **Mean/m** & **Median/m** & **Min/m** & **Rmse/m** & **Sse/m2** & **Std/m** \\ \hline ORB-SLAM3 & 0.016234 & 0.004784 & 0.004304 & 0.000483 & 0.005695 & 0.004995 & 0.003091 \\ Our & 0.019639 & 0.005585 & 0.004463 & 0.000445 & 0.006751 & 0.006563 & 0.003787 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Average relative trajectory error. Figure 14: The fr1_xyz sequence data: (**a**) sparse mapping; (**b**) dense mapping; (**c**) OctoMap. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Sequence** & **Duration/s** & **Length/m** & \
\begin{tabular}{c} **Avg.** \\ **Translational** \\ **Velocity/(m\(\cdot\)s\({}^{-1}\))** \\ \end{tabular} &
\begin{tabular}{c} **Avg. Angular** \\ **Velocity** \\ **(deg\(\cdot\)s\({}^{-1}\))** \\ \end{tabular} \\ \hline fr1\_desk & 23.40 & 9.263 & 0.413 & 23.327 \\ fr1\_xyz & 30.09 & 7.112 & 0.244 & 8.920 \\ fr2\_xyz & 122.74 & 7.029 & 0.058 & 1.716 \\ fr2\_desk & 99.36 & 18.880 & 0.193 & 6.338 \\ fr3\_long\_office & 87.09 & 21.455 & 0.249 & 10.188 \\ fr3\_walk\_rpy & 30.61 & 2.698 & 0.091 & 20.903 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: TUM dataset parameters. Figure 13: The fr1_desk sequence data: (**a**) sparse mapping; (**b**) dense mapping; (**c**) OctoMap. Figure 16: The fr2_desk sequence data: (**a**) sparse mapping; (**b**) dense mapping; (**c**) OctoMap. Figure 15: The fr2_xyz sequence data: (**a**) sparse mapping; (**b**) dense mapping; (**c**) OctoMap. Sparse maps for small-scale indoor scenes (such as fr1_desk and fr1_xyz) consist solely of essential feature points, which, although they can represent fundamental spatial patterns, have limitations in detail representation. Conversely, dense point cloud maps may fully rebuild rigid entities such as desktops and keyboards and precisely depict extensive planar structures like walls and floors. Moreover, the voxelized representation post-OctoMap conversion enhances the spatial structure, distinctly illustrating variations across different height strata, with color gradients rendering spatial elevation changes readily observable. In more extensive scenarios (such as fr2_desk and fr2_xyz), despite heightened scene complexity, the system sustains a consistent mapping performance.