# Semantic Visual SLAM Algorithm Based on Improved DeepLabV3+ Model and LK Optical Flow
## 4 Experimental Results
### Analysis of Experimental Results
#### 4.3.3 Positioning Accuracy Experiments in an Indoor Dynamic Environment  
(1) Positioning accuracy experiments  
The ORB-SLAM2 system, the proposed improved algorithm, and other advanced SLAM algorithms applied to dynamic scenes were run on the above dataset, and the camera position estimated by the improved algorithm was compared with the real position provided by the dataset. The test metrics include absolute trajectory error and relative position error. The statistics include Root Mean Square Error (RMSE), mean of error (mean), median of error (median), and Standard Deviation (STD). To calculate the difference, the timestamps were aligned on three scales: translation, rotation, and scale scaling, and the lift rate is calculated by Equation (14). \[\eta=\left(1-\frac{e}{o}\right)\times 100\% \tag{14}\]  
where \(\eta\) is the lift rate, \(o\) is the operation result of the comparison algorithm, and \(e\) is the operation result of the proposed improved algorithm. Tables 5-7 show the comparisons of the absolute trajectory error, relative position translation error, and relative position rotation error between the improved algorithm and ORB-SLAM2, and all the values are averaged over five samples. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Sequence**} & \multicolumn{4}{c}{**ORB-SLAM2**} & \multicolumn{4}{c}{**Proposed Algorithm**} \\ \cline{2-9}  & **RMSE** & **Mean** & **Median** & **STD** & **RMSE** & **Mean** & **Median** & **STD** \\ \hline walking\_xyz & 1.1259 & 0.9219 & 0.8314 & 0.6464 & 0.0242 & 0.0210 & 0.0188 & 0.0120 \\ walking\_rpy & 1.0650 & 0.8958 & 0.8578 & 0.5761 & 0.0550 & 0.0444 & 0.0348 & 0.0326 \\ walking\_halfsphere & 0.4112 & 0.3222 & 0.3893 & 0.2556 & 0.0112 & 0.0101 & 0.0094 & 0.0049 \\ walking\_static & 0.5698 & 0.3933 & 0.0781 & 0.4123 & 0.0092 & 0.0089 & 0.0079 & 0.0039 \\ sitting\_static & 0.0115 & 0.0102 & 0.0093 & 0.0054 & 0.0096 & 0.0086 & 0.0080 & 0.0042 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of the relative positional translation error (unit: m). \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Sequence**} & \multicolumn{4}{c}{**ORB-SLAM2**} & \multicolumn{4}{c}{**Proposed Algorithm**} \\ \cline{2-9}  & **RMSE** & **Mean** & **Median** & **STD** & **RMSE** & **Mean** & **Median** & **STD** \\ \hline walking\_xyz & 21.4560 & 17.6484 & 16.1745 & 12.2021 & 0.6719 & 0.5168 & 0.4311 & 0.4293 \\ walking\_rpy & 18.9632 & 15.0722 & 12.5163 & 11.5080 & 1.2563 & 1.0028 & 0.7651 & 0.7567 \\ walking\_halfsphere & 8.0912 & 6.5589 & 8.3318 & 4.7380 & 0.2757 & 0.2507 & 0.2390 & 0.1147 \\ walking\_static & 10.2478 & 7.0801 & 1.2399 & 7.4087 & 0.3177 & 0.2845 & 0.2650 & 0.1413 \\ sitting\_static & 0.3565 & 0.3210 & 0.2990 & 0.1550 & 0.3194 & 0.2870 & 0.2709 & 0.1401 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Comparison of the relative positional rotation error (unit: degree). \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Sequence**} & \multicolumn{4}{c}{**ORB-SLAM2**} & \multicolumn{4}{c}{**Proposed Algorithm**} \\ \cline{2-9}  & **RMSE** & **Mean** & **Median** & **STD** & **RMSE** & **Mean** & **Median** & **STD** \\ \hline walking\_xyz & 0.7670 & 0.6578 & 0.5515 & 0.3945 & 0.0168 & 0.0142 & 0.0124 & 0.0089 \\ walking\_rpy & 0.6942 & 0.5912 & 0.4471 & 0.3639 & 0.0380 & 0.0309 & 0.0245 & 0.0222 \\ walking\_halfsphere & 0.2736 & 0.2447 & 0.2287 & 0.1224 & 0.0077 & 0.0069 & 0.0062 & 0.0034 \\ walking\_static & 0.3974 & 0.3619 & 0.3002 & 0.1641 & 0.0062 & 0.0055 & 0.0051 & 0.0028 \\ sitting\_static & 0.0079 & 0.0070 & 0.0062 & 0.0038 & 0.0066 & 0.0058 & 0.0053 & 0.0030 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Comparison of the absolute trajectory error (unit: m). As can be seen from Tables 5-7, the proposed improved algorithm performs significantly better than the ORB-SLAM2 algorithm in highly dynamic scenarios (walking).