# Robotic System for Post Office Package Handling
## 4 Results and Discussion  
The described system was implemented in the lab environment and validated for post office parcel handling in multiple scenarios, illustrated in Figure 6. The experiments were conducted in five different scenarios, each consisting of a different amount of packages, and the system was tested for its ability to clear the workspace. The physical setup of the robot is depicted in Figure 3. The robot is located near the table holding a pile of realistic parcels--see Figure 5a--and they should be moved to a container standing nearby. The camera is mounted approximately 1 m above the table. Figure 5: Dex-Net input and output. It takes an RGBD image of the object pile as input and produces a grasp point. Five scenarios, consisting of 1, 5, 10, 15 and 20 parcels in the workspace, were used for testing. Each scenario was tested 10 times, and the packages were randomly distributed in the workplace. The packages were piled on top of each other when possible to replicate real-life setups as much as possible. The attempts for each scenario were counted and compared to the expected amount, which was set to one attempt per package in the scenario. Afterward, the average deviation from the expected attempt amount was calculated and, lastly, an overall average deviation was calculated to see the mean error of the system. The results can be seen in Table 1.  
As per results, the 1-package scenario showed a perfect score, 5 packages resulted in an average of 5.3 attempts per 5 packages, for 10 packages, it took an average of 10.4 attempts, for 15 packages, an average of 16 attempts were needed, and, for 20 packages, an average of 21.3 attempts was required. Overall, the system achieved a 100% success rate for emptying the workspace, meaning that all the packages were successfully handled; however, an average of a 4.37% increase in additional grasps can be observed when compared to the perfect one attempt per package. By measuring only one attempt per package, the system succeeded with 94.1% successful grasps. Even though some grasps did not achieve success, the system could recover and grasp the object on the second try. While testing, it was observed that most of the failed attempts can be attributed to a grasp pose located on an uneven part where the vacuum gripper cannot achieve the required vacuum to grasp the desired package. This issue could be addressed by a more flexible vacuum cap or increasing the vacuum, whereas the available hardware in this experimental setup was already adjusted as much as possible for these experiments. A customized vacuum system for a specific use-case and package materials could increase the average grasping success rates. To the best of the author's knowledge, there is no relevant literature available on the post office parcel-handling process; however, the available similar systems working with unknown and arbitrarily placed objects show similar precision ratings [22; 23; 24]. Furthermore, the developed system experimentally proves the viability of the robotic system for deployments in complex scenarios, where the objects can be very similar but also differ in terms of size and materials. In a real use case, there would be a conveyor belt in place of the container. The system was tested with different pile configurations and parcel types, and, in all cases, the system \begin{table}
\begin{tabular}{c c c c} \hline
**Scenario, Packages** & **Grasp Attempts, Average** & **Additional Grasps** & **Success Rate** \\ \hline
1 & 1 & 0.00\% & 100\% \\
5 & 5.3 & 5.66\% & 100\% \\
10 & 10.4 & 3.85\% & 100\% \\
15 & 16 & 6.25\% & 100\% \\
20 & 21.3 & 6.10\% & 100\% \\ \hline \multicolumn{4}{c}{Overall additional grasps} & 4.37\% \\ \hline \end{tabular}
\end{table} 
Table 1: Experimental results. Figure 6: Testing scenario examples. From left to right, 1, 5, 10, 15, 20 packages in the workspace.