Vision-based pose estimation for indoor navigation of unmanned micro aerial vehicle based on the 3D model of environment

Author(s):  
Alexander Buyval ◽  
Mikhail Gavrilenkov
Robotics ◽  
2017 ◽  
Vol 6 (2) ◽  
pp. 6 ◽  
Author(s):  
Haiwen Yuan ◽  
Changshi Xiao ◽  
Supu Xiu ◽  
Yuanqiao Wen ◽  
Chunhui Zhou ◽  
...  

Author(s):  
Hanoch Efraim ◽  
Amir Shapiro ◽  
Moshe Zohar ◽  
Gera Weiss

In this work, we suggest a novel solution to a very specific problem—calculating the pose (position and attitude) of a micro-aerial vehicle (MAV) operating inside corridors and in front of windows. The proposed method makes use of a single image captured by a front facing camera, of specific features whose three-dimensional (3D) model is partially known. No prior knowledge regarding the size of the corridor or the window is needed, nor is the ratio between their width and height. The position is calculated up to an unknown scale using a gain scheduled iterative algorithm. In order to compensate for the unknown scale, an adaptive controller that ensures consistent closed loop behavior is suggested. The attitude calculation can be used as is, or the results can be fused with angular velocity sensors to achieve better estimation. In this paper, the algorithm is presented and the approach is demonstrated with simulations and experiments.


2012 ◽  
Author(s):  
James Joo ◽  
Gregory Reich ◽  
James Elgersma ◽  
Kristopher Aber

Author(s):  
Jinwoo Jeon ◽  
Sungwook Jung ◽  
Eungchang Lee ◽  
Duckyu Choi ◽  
Hyun Myung

2021 ◽  
Vol 11 (5) ◽  
pp. 2347 ◽  
Author(s):  
Jorge Solis ◽  
Christoffer Karlsson ◽  
Simon Johansson ◽  
Kristoffer Richardsson

This research aims to develop an automatic unmanned aerial vehicle (UAV)-based indoor environmental monitoring system for the acquisition of data at a very fine scale to detect rapid changes in environmental features of plants growing in greenhouses. Due to the complexity of the proposed research, in this paper we proposed an off-board distributed control system based on visual input for a micro aerial vehicle (MAV) able to hover, navigate, and fly to a desired target location without considerably affecting the effective flight time. Based on the experimental results, the MAV was able to land on the desired location within a radius of about 10 cm from the center point of the landing pad, with a reduction in the effective flight time of about 28%.


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