# Social and Robust Navigation for Indoor Robots Based on Object Semantic Grid and Topological Map
## 6 Experimental Results
### Segmented Global Path Planning Results  
The segmented global path planning method with topological map and auxiliary navigation points aims to improve the success rate and safety of domestic navigation and decrease the computational time. The experiments were grouped into the test on the success rate and the test on global path planning efficiency to evaluate the method.  
To compare the performance of the success rate, the crossing door success rate (CDSR) and navigation success rate (NSR) was employed as standard. The CDSR indicates the door number passed successfully divided by the total door number. If the robot collides with the door frame or cannot plan the path in the process of passing door, it is considered that the robot fails to pass the door. Furthermore, in terms of the likelihood of collision to other obstacles leading to navigation termination, NSR is defined and indicates the number of successful navigation paths divided by the total number of navigation paths. If the robot reaches the destination and does not collide with other objects during the whole navigation process, the robot navigation is successful. The higher NSR and CDSR indicate better performance.  
To assess the improvement of global path planning efficiency, we defined the path length and the traversed cells number. The shorter the planned path, the better the algorithm. To improve the efficiency of planning, the less time the algorithm consumes, the better the algorithm. In addition to considering that different computers have different performances and the time consumed mainly depends on the number of traversed cells (the cells whose potential has been calculated) by the path planning algorithm, we used the number of traversed cells to evaluate the efficiency of our system.  
_Appl. Sci._**2020**, _10_, 8991  
\begin{table}
\begin{tabular}{|p{142.3 pt}|} \hline
**Word Segmentation** & **Selecting Navigation Goal 1** & **Navigation Result** \\ \hline
**Speech to text and Separate**: go to the/front/ of/sink/ in the/bathroom & \\
**Room goal:** bathroom & \\
**Object goal:** sink & \\
**Location goal:** front & \\ \hline
**Speech to text and Separate**: go to the/side/ of/sink/ in the/bathroom & \\
**Room goal:** bathroom & \\
**Object goal:** sink & \\
**Location goal:** side & \\ \hline
**Speech to text and Separate**: go to the/front/ of/TV/ in the/livingroom & \\
**Room goal:** livingroom & \\
**Object goal:** sink & \\
**Location goal:** sink & \\ \hline
**Speech to text and Separate**: go to the/side/ of/TV/ in the/livingroom & \\
**Room goal:** livingroom & \\
**Object goal:** sink & \\
**Location goal:** sink & \\ \hline
**Speech to text and Separate**: go to the/side/ of/ridge/ in the/kitchen & \\
**Room goal:** kitchen & \\
**Object goal:** fridge & \\
**Location goal:** side & \\ \hline
**Speech to text and Separate**: go to the/front/ of/laptop/ in the/meetingroom & \\
**Room goal:** meetingroom & \\
**Object goal:** laptop & \\
**Location goal:** front & \\ \hline
**Speech to text and Separate**: go to the/side/ of/ microwave/ in the/LAB & \\
**Room goal:** LAB & \\
**Object goal:** microwave & \\
**Location goal:** side & \\ \hline \end{tabular}
\end{table}
Table 3: Experiment results of automatically selecting navigation goal.