# Mixed Reality Enhanced User Interactive Path Planning for Omnidirectional Mobile Robot
## 6 Experimental Results and Analysis
### Path Planning without Virtual Obstacles  
This part of the experiment tested the actual effect of the proposed path planning algorithm on the known map without virtual obstacles added. The map adopted was a 16 \(\times\) 28 m simulation environment, in which we put some fixed obstacles to test the effect of obstacle avoidance. One starting point and two target points were set, which made the planning path longer and the experimental results more universal. In order to better show the experimental effect, we used a dynamic window approach (DWA) in the ROS navigation package as the comparison algorithm under the condition that other variables were the same.  
Based on two different path planning algorithms, the mobile robot started from the same point on the map and passed through two target points, respectively. The trajectory generated on RViz was shown in the Figure 8. The comparison of trajectory coordinates is shown in the Figure 9a. As can be seen from the figures, both algorithms can enable the mobile robot to successfully avoid obstacles and reach the target point. But the improved VFH* produces a smoother trajectory, which makes the movement smoother. On the other hand, the trajectory generated by the proposed algorithm distance from the obstacle was safer. When a narrow passage was encountered, the middle safer trajectory was chosen.  
Figure 6: The virtual panel in Unity3D.  
Figure 7: Diagram of software and communication layout.  
The comparison of the changes in velocity and angular velocity of the two algorithms in the process of motion is shown in Figure 9b,c. When adopting the algorithm proposed in this paper, the maximum and minimum of velocity and angular velocity respectively, were limited, and the deceleration when obstacles were detected was optimized, so that it would not be reduced to zero directly. In this way, the mechanical motion structure of the mobile robot can be better protected and the moving process can be smoother. Meanwhile, by comparing the two figures, it can be seen that the two curves suddenly changed at the same time: when the mobile robot detected obstacles to avoid.  
Additionally, as can be seen from Table 1, under the premise of setting the same starting point and target points, the improved method in this paper produces shorter path lengths, shorter robot movement time than the traditional DWA method, and the sum of the distances to the obstacles is further when the robot passes the same number of obstacles.  
The improved algorithm proposed in this paper was effective in this experiment. The mobile robot could smoothly avoid obstacles and safely reach the specified target point. Besides, the changes of velocity and angular velocity were flexible and the system was robust.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Methods** & **DWA** & **The Improved VFH*** \\ \hline Path length (m) & 17.91 & 17.36 \\ Run time (s) & 64.6 & 62.2 \\ Passing obstacle & 5 & 5 \\ Sum of the distance & 2.95 & 3.40 \\ from the obstacle (m) & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Experimental results of parameters in the path planning without virtual obstacles.  
Figure 8: Trajectory comparison in RViz. (**a**) Trajectory using the DWA algorithm. (**b**) Trajectory using the improved VFH* algorithm.  
Figure 9: The results of different path planning methods were compared in the experiment I. (**a**) The trajectory comparison. (**b**) The velocity comparison. (**c**) The angular velocity comparison.