## 4 Discussion and Conclusions  
Visual data can be beneficial for autonomous landing because it can resolve issues related to inaccurate GPS navigation and GPS-denied environments. This study proposed a new autonomous landing system optimized for MAVs. The developed landing platform was designed with various equipment to assist landing: a spherical object for searching from long distances, align markers, and a camera for position adjustment. A new algorithm was developed to improve the detection of spherical objects on the platform. It was verified that the new detection algorithm could accurately detect spherical objects under harsh lighting environments. Eighty flight experiments were conducted to validate the performance of the proposed landing system. All landing trials were successful, with an average position error of 2.7 \(\pm\) 1.4 cm. Moreover, the entire landing procedure (i.e., search, approach, and landing) was completed in a short time (26 s on average). Therefore, the proposed landing system enables the MAV to perform robust and precise landing; the MAV requires only a single RGB vision camera and does not require any additional sensors. Although a laptop was used to operate the object detection algorithm in the present study, in future work, the proposed algorithm can be executed on the MAV on-board computing as this algorithm requires minimal computational resources. Specifically, the entire computation (i.e., feedback control of the MAV and image processing on the images from camera 1 and 2) was conducted on a laptop with Intel Core i5 3317U (dual core, 1.7 GHz). In the future, the detection algorithm can be implemented in an MAV with an onboard computing device. For example, a microcontroller with quad core Cortex-A72 can be used because its computing power is similar to the laptop used in this study. Furthermore, it is worth noting that the microcontroller in the MAV does not need to conduct detection for the align marker. Because this process aims to detect three markers simultaneously, it requires heavier computation. This process can be performed by the laptop connected to the landing platform. Therefore, in the future, an MAV with onboard computing will be able to achieve a fast and accurate landing in collaboration with the extra computing device embedded in the platform. Despite the high accuracy and success rate in the experiments, there are some limitations to be considered. The detection algorithm depends on the color of the target object. Thus, if an object has a similar color to that of the target object, the algorithm can erroneously predict the other spherical object as the target object. The disrupting object, which has a similar color to that of the target object, is mostly smaller than the target din images. Thus, to reduce the misdetection, the algorithm was designed to predict the largest object as the target object among the candidate objects with similar colors. Details on this limitation are provided in Supplementary Material. Moreover, because all the experiments were conducted indoors, outdoor environmental conditions, such as wind and weather, \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Initial Position** & **STEP 1** & **STEP 2** & **STEP 3 \& **4** & **STEP 5** & **STEP 6** & **Total** \\ \hline L1 & 2.5 & 9.4 & 2.4 & 0.5 & 9.1 & 23.9 \\ L2 & 2.5 & 8.5 & 2.8 & 4.0 & 7.3 & 25.1 \\ L3 & 2.6 & 8.9 & 3.0 & 6.0 & 5.7 & 26.1 \\ L4 & 2.5 & 8.9 & 2.6 & 6.5 & 5.0 & 25.4 \\ L5 & 2.6 & 9.6 & 2.6 & 10.1 & 5.0 & 29.9 \\ L6 & 2.5 & 10.5 & 2.6 & 7.2 & 4.9 & 27.8 \\ L7 & 2.4 & 9.2 & 2.3 & 5.8 & 5.2 & 24.8 \\ L8 & 2.4 & 10.4 & 2.3 & 3.2 & 6.4 & 24.6 \\ Average & 2.5 & 9.4 & 2.6 & 5.4 & 6.1 & 26.0 \\ \hline \hline \end{tabular} Units: s.  
\end{table} 
Table 3: Average time required during the landing procedure. Ten trials were conducted for every direction. can degrade the landing performance. Additional experiments are necessary to verify the proposed landing system under various weather conditions. The MAV can also collide with a spherical object during searching.