Stereo Vision based Relative Pose and Motion Estimation for Unmanned Helicopter Landing

Xu, Cui; Qiu, Liankui; Liu, Ming; Kong, Bin; Ge, Yaojun

doi:10.1109/icia.2006.306029

Cited by 23 publications

(13 citation statements)

References 8 publications

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“…The study on helicopter landing has been a hotspot in recent years. The estimation of position and altitude [8,9], landing in unusual conditions [10], and visualization [11,12] are the main concerns. In Reference [13], the movement state estimation method based on the vision image process for unmanned helicopters is proposed.…”

Section: Literature Review and The Work Of This Papermentioning

confidence: 99%

Path Planning for Autonomous Landing of Helicopter on the Aircraft Carrier

et al. 2018

Mathematics

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Helicopters are introduced on the aircraft carrier to perform the tasks which are beyond the capability of fixed-wing aircraft. Unlike fixed-wing aircraft, the landing path of helicopters is not regulated and can be determined autonomously, and the path planning problem for autonomous landing of helicopters on the carrier is studied in this paper. To solve the problem, the returning flight is divided into two phases, that is, approaching the carrier and landing on the flight deck. The feature of each phase is depicted, and the conceptual model is built on this basis to provide a general frame and idea of solving the problem. In the established mathematical model, the path planning problem is formulated into an optimization problem, and the constraints are classified by the characteristics of the helicopter and the task requirements. The goal is to reduce the terminal position error and the impact between the helicopter and the flight deck. To obtain a reasonable landing path, a multiphase path planning algorithm with the pigeon inspired optimization (MPPIO) algorithm is proposed to adapt to the changing environment. Three experiments under different situations, that is, static carrier, only horizontal motion of carrier considered, and 3D motion of carrier considered, are conducted. The results demonstrate that the helicopters can all reach the ideal landing point with the reasonable path in different situations. The small terminal error and relatively vertical motion between the helicopter and the carrier ensure a precise and safe landing.

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Section: Literature Review and The Work Of This Papermentioning

confidence: 99%

Path Planning for Autonomous Landing of Helicopter on the Aircraft Carrier

et al. 2018

Mathematics

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“…An on-board binocular vision-based system presented in [37] estimated the relative pose between two drones to verify the autonomous aerial refueling of UAVs. Xu et al [38] proposed a real-time stereo vision-based pose estimation system for an unmanned helicopter landing on a moving target. The geometry features of 2D planer targets are used to simplify the process of feature extraction.…”

Section: Introductionmentioning

confidence: 99%

Aircraft Pose Estimation Based on Geometry Structure Features and Line Correspondences

Teng

Luo

et al. 2019

Sensors

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A robust and accurate aircraft pose estimation method is proposed in this paper. The aircraft pose reflects the flight status of the aircraft and accurate pose measurement is of great importance in many aerospace applications. This work aims to establish a universal framework to estimate the aircraft pose based on generic geometry structure features. In our method, line features are extracted to describe the structure of an aircraft in single images and the generic geometry features are exploited to form line groups for aircraft structure recognition. Parallel line clustering is utilized to detect the fuselage reference line and bilateral symmetry property of aircraft provides an important constraint for the extraction of wing edge lines under weak perspective projection. After identifying the main structure of the aircraft, a planes intersection method is used to obtain the 3D pose parameters based on the established line correspondences. Our proposed method can increase the measuring range of binocular vision sensors and has the advantage of not relying on 3D models, cooperative marks or other feature datasets. Experimental results show that our method can obtain reliable and accurate pose information of different types of aircraft.

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“…In the work of Saito et al (2007), cameraimage based relative pose and motion estimation for unmanned helicopter were discussed. In the works of Katzourakis et al (2009) and Xu et al (2006), navigation and landing with the stereo vision system was discussed. Xu et al used the stereo vision system for estimating the position of the body.…”

Section: Introductionmentioning

confidence: 99%