Real-time 6DoF deck pose estimation and target tracking for landing an UAV in a cluttered shipboard environment using on-board vision

Lin, Shanggang; Garratt, Matthew A.; Lambert, Andrew

doi:10.1109/icma.2015.7237532

Cited by 7 publications

(2 citation statements)

References 15 publications

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“…Placing artificial patterns or objects provides knowledge about the scene, which facilitates motion recovery [2], [3]. However, these methods demand the observation of the target for effective estimation.…”

Section: Introductionmentioning

confidence: 99%

Inertial-aided state and slope estimation using a monocular camera

Garratt

Lambert

2015

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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This paper aims at estimating the metric state of a quadrotor using a monocular camera and an Inertial Measurement Unit (IMU) based on a homography model. Angular velocities are obtained from the on-board IMU and subtracted from the homography matrix. The reshaped vector from the homography matrix is directly fused with acceleration measurements using an Extended Kalman Filter. The visual inertial fusion framework is capable of estimating distance to the plane, speed, acceleration biases and surface normal. The feasibility of our method is proven using simulation and on real sensory data recorded from our quadrotor platform. It is shown that our approach is superior over traditional method that decomposes the homography matrix for the estimation of surface normal.

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Section: Introductionmentioning

confidence: 99%

Inertial-aided state and slope estimation using a monocular camera

Garratt

Lambert

2015

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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“…With regards UAV's autonomous landing, computer vision has been covered in the literature through two main approaches: (a) the detection of natural environment (using line features detection of natural scenes [29] or natural landmarks [30]); (b) the use of artificial markers, where an element with a specific imagen pattern is placed in the landing region to be discovered and provide positioning and orientation (traditional "H-shape" [31], square-shaped [32], specially ARTag [33], ApriTag [34], and ArUco [35][36][37]). Indoors, especially in manufacturing plants, requires artificial markers to be deployed to allow pattern recognition and support landing.…”

Section: Introduction and State Of The Artmentioning

confidence: 99%

Methodology for Indoor Positioning and Landing of an Unmanned Aerial Vehicle in a Smart Manufacturing Plant for Light Part Delivery

et al. 2020

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Unmanned aerial vehicles (UAV) are spreading their usage in many areas, including last-mile distribution. In this research, a UAV is used for performing light parts delivery to workstation operators within a manufacturing plant, where GPS is no valid solution for indoor positioning. A generic localization solution is designed to provide navigation using RFID received signal strength measures and sonar values. A system on chip computer is onboarded with two missions: first, compute positioning and provide communication with backend software; second, provide an artificial vision system that cooperates with UAV’s navigation to perform landing procedures. An Industrial Internet of Things solution is defined for workstations to allow wireless mesh communication between the logistics vehicle and the backend software. Design is corroborated through experiments that validate planned solutions.

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An efficient vision-based pose estimation algorithm using the assistant reference planes based on the perspective projection rays

Zhang

2018

Sensors and Actuators A: Physical

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Real-time 6DoF deck pose estimation and target tracking for landing an UAV in a cluttered shipboard environment using on-board vision

Cited by 7 publications

References 15 publications

Inertial-aided state and slope estimation using a monocular camera

Inertial-aided state and slope estimation using a monocular camera

Methodology for Indoor Positioning and Landing of an Unmanned Aerial Vehicle in a Smart Manufacturing Plant for Light Part Delivery

An efficient vision-based pose estimation algorithm using the assistant reference planes based on the perspective projection rays

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