A New Combined Vision Technique for Micro Aerial Vehicle Pose Estimation

Yuan, Haiwen; Xiao, Changshi; Xiu, Supu; Wen, Yuanqiao; Zhou, Chunhui; Li, Qiliang

doi:10.3390/robotics6020006

Cited by 6 publications

(2 citation statements)

References 26 publications

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“…For this purpose, a hierarchical detection and localization framework is proposed and studied to detect and extract various scale features from the landing object. In one of our preliminary works, a UAV autonomous visual navigation system was reported in [25].…”

Section: Previous Workmentioning

confidence: 99%

A Hierarchical Vision-Based UAV Localization for an Open Landing

et al. 2018

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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.

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Section: Previous Workmentioning

confidence: 99%

A Hierarchical Vision-Based UAV Localization for an Open Landing

et al. 2018

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“…Wenzel et al 32 used a Wii remote IR camera as main sensor, which allows robust tracking of a pattern of IR lights in conditions without direct sunlight. In our preliminary work, one multi-view navigation system 33 has also been reported, that employed hybrid vision measurements to estimate UAV pose.…”

Section: Previous Workmentioning

confidence: 99%

A hierarchical vision-based localization of rotor unmanned aerial vehicles for autonomous landing

Yuan

Xiao

Xiu

et al. 2018

International Journal of Distributed Sensor Networks

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The vision-based localization of rotor unmanned aerial vehicles for autonomous landing is challenging because of the limited detection range. In this article, to extend the vision detection and measurement range, a hierarchical vision-based localization method is proposed for unmanned aerial vehicle autonomous landing. In such a hierarchical framework, the landing is defined into three phases: “Approaching,”“Adjustment,” and “Touchdown,” in which visual artificial features at different scales can be detected from the designed object pattern for unmanned aerial vehicle pose recovery. The corresponding feature detection and pose estimation algorithms are also presented. In the end, typical simulation and field experiments have been carried out to illustrate the proposed method. The results show that our hierarchical vision-based localization has the ability to a consecutive unmanned aerial vehicle localization in a wider working range from far to near, which is significant for autonomous landing.

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