Abstract
The localization of unmanned aerial vehicles (UAVs) for autonomous landing is challenging because the relative positions of the landing objects are almost inaccessible and the objects have nearly no transmission with UAVs. In this paper, a hierarchical vision-based localization framework for rotor UAVs is proposed for an open landing. In such a hierarchical framework, the landing is defined into three phases: “Approaching”, “Adjustment”, and “Touchdown”. Object features at different scales can be extracted from a designed Robust and Quick Response Landing Pattern (RQRLP) and the corresponding detection and localization methods are introduced for the three phases. Then a federated Extended Kalman Filter (EKF) structure is costumed and utilizes the solutions of the three phases as independent measurements to estimate the pose of the vehicle. The framework can be used to integrate the vision solutions and enables the estimation to be smooth and robust. In the end, several typical field experiments have been carried out to verify the proposed hierarchical vision framework. It can be seen that a wider localization range can be extended by the proposed framework while the precision is ensured.
Highlights
Unmanned aerial vehicles (UAVs) are popular among civil and military situations that are hazardous to human operators
This paper describes a vision-based localization framework and the key enabling technologies for an open landing
This paper describes a hierarchical vision-based unmanned aerial vehicles (UAVs) localization demonstration in which the pose can be estimated by using the onboard camera
Summary
Haiwen Yuan 1,2, * ID , Changshi Xiao 1,3,4, *, Supu Xiu 1 , Wenqiang Zhan 1 ID , Zhenyi Ye 2 , Fan Zhang 1,3,4 , Chunhui Zhou 1,3,4 , Yuanqiao Wen 1,3,4 and Qiliang Li 2, *. Hubei Key Laboratory of Inland Shipping Technology, Wuhan University of Technology, Wuhan 430063, China
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