# Vision-Guided Hierarchical Control and Autonomous Positioning for Aerial Manipulator
## 6 Conclusions  
This paper describes the design of a lightweight, single-degree-of-freedom aerial manipulator platform with a simple structure, implements a hierarchical control approach, and proposes a laser SLAM localization method integrated with IMU. By employing a segmented grasping strategy using a visual guidance algorithm, the successful grasping of target objects was achieved. The proposed SLAM-based autonomous navigation algorithm offered higher localization accuracy and greater reliability for UAVs with manipulator disturbances. Finally, the platform exhibited excellent flight stability and operational capabilities. This study provides valuable insights into the practical applications of future aerial manipulators and expands the scope of drone operations.  
Our future work will focus primarily on the following research areas:  
1. The proposed hierarchical control method failed to effectively address the coupling interaction between the manipulator and the UAV. Therefore, a coupling control method with good control effectiveness will be implemented onto the actual hardware platform.
2. The designed manipulator has a single degree of freedom and only grasps lightweight cylindrical objects. In the future, the structure of the manipulator and its end effector can be improved to achieve the grasping of objects in arbitrary poses.
3. The onboard computer Jetson Xavier NX in our system is tasked with multiple functions, however, its computational capabilities are limited. To conserve computational resources and improve the accuracy of target object detection, we will incorporate deep learning and lightweight neural network algorithms [40].
4. Considering that the motion of the robotic arm can alter the system's center of gravity, affecting stability, the combination of the manipulator and a tilt-rotor UAV [41] can be considered to provide real-time compensation to address the system's offset center of gravity. Additionally, the current position of the target object is pre-known, however, it can be autonomously obtained by installing a camera on the manipulator and providing real-time feedback [42], facilitating the dynamic tracking and capturing of moving targets. This will allow for the adjustment of the length and position of the manipulator, improving the grasping success rate.
5. Although we have focused on the control system of the aerial manipulator and the autonomous positioning and navigation system, improvements are required to address complex scenarios for various applications. In the future, consideration will be given to optimizing the motor torque of the robotic arm and the structure of the end effector to meet the practical application requirements of the flying robotic arm.  
Conceptualization, X.Y. and H.C.; methodology, L.W.; software (Ubuntu20.04 Python3.11), H.C., S.X. and H.N.; writing--original draft preparation, L.W. and X.Y.; writing--review and editing, L.W. and X.Y. All authors have read and agreed to the published version of the manuscript.  
This work is sponsored by the National College Student Innovation and Entrepreneurship Training Program (202310346043); General Projects of Zhejiang Provincial Department of Education (Y202353307).  
Not applicable.  
Data Availability Statement: Data are contained within the article.  
The author declares no conflict of interest.