Abstract
Unmanned aerial manipulator (UAM) that integrates an unmanned aerial vehicle (UAV) and an aerial manipulator extends the capability of the underlying UAV to a wide range of potential applications, such as flexible inspection, interactive manipulation, and scientific sampling. Typical challenges faced by UAM surveillance include maintaining a surveillance distance, eliminating disturbances caused by model uncertainties and the external environment, and adjusting the camera’s orientations. Focused on the development of autonomous control for UAM during a process of flexible inspection, this paper presents a novel control scheme for autonomous inspection that is required to cope with model uncertainties and external disturbances. First, surveillance waypoints are obtained with respect to inspective objects and the radius of geometric relationship. In particular, the desired linear velocities are obtained through consideration of the angular velocity of the surveillance and the objective inspective radius. A robust controller is designed to ensure the tracking performance of the given UAM. Second, a disturbance observer is adopted to eliminate the model uncertainties and external disturbances. Finally, according to inspection requirements, the orientation of the onboard manipulator is adjusted so that the end effector (camera) of orientation is towards the object sustainably. The stability analysis of the proposed controller is provided. Experimental simulations demonstrate that the proposed approach enables the UAM to accurately track prescribed waypoints.
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Acknowledgment
This work was partially supported by the National Natural Science Foundation of China (Project No. 61803089) and the Natural Science Foundation of Fujian Province (No. 2019J01213).
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Zhan, W., Chen, Y., Wang, Y., Chao, F., Shen, Q. (2022). Robust Control for Autonomous Surveillance with Unmanned Aerial Manipulator. In: Jansen, T., Jensen, R., Mac Parthaláin, N., Lin, CM. (eds) Advances in Computational Intelligence Systems. UKCI 2021. Advances in Intelligent Systems and Computing, vol 1409. Springer, Cham. https://doi.org/10.1007/978-3-030-87094-2_19
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