Monocular vision-based iterative pose estimation algorithm from corresponding feature points

2010 ◽  
Vol 53 (8) ◽  
pp. 1682-1696 ◽  
Author(s):  
ShiJie Zhang ◽  
XiBin Cao ◽  
Fan Zhang ◽  
Liang He
Sensors ◽  
2016 ◽  
Vol 16 (12) ◽  
pp. 2173 ◽  
Author(s):  
Zimiao Zhang ◽  
Shihai Zhang ◽  
Qiu Li

2013 ◽  
Vol 333-335 ◽  
pp. 268-274
Author(s):  
Jing Jing Wang ◽  
Jian Yu Huang ◽  
Shi Yin Qin

In this paper, a high accuracy and efficiency pose estimation algorithm is proposed for space cooperative targets in RVD based on binocular visual measurement. At first, the scheme of visual measurement toward RVD is presented and the environment conditions and performance requirement are analysed and discussed. Then the relationship of pose estimation with detection and tracking is studied to give an implementing strategy of pose estimation with high accuracy and efficiency. Moreover, the key point is focused on the pose estimation of cooperative targets, in which a stereo vision mapping relation between three dimensionl coordinates of spacial feature points of cooperative targets and their corresponding image coordinates is established, then the least square method is employed to estimate the three-dimensional coordinates of feature points so as to calculate the relative position and attitude between tracking spacecraft and target spacecraft with high precision, finally a series of experimental resluts indicate that the proposed pose estimation algorithm under binocular visual measurement demonstrates well performance in the estimation accuracy, anti-noise and real-time thus can achieve the application requriements of RVD under binocular visual measurement.


2007 ◽  
Vol 111 (1120) ◽  
pp. 389-396 ◽  
Author(s):  
G. Campa ◽  
M. R. Napolitano ◽  
M. Perhinschi ◽  
M. L. Fravolini ◽  
L. Pollini ◽  
...  

Abstract This paper describes the results of an effort on the analysis of the performance of specific ‘pose estimation’ algorithms within a Machine Vision-based approach for the problem of aerial refuelling for unmanned aerial vehicles. The approach assumes the availability of a camera on the unmanned aircraft for acquiring images of the refuelling tanker; also, it assumes that a number of active or passive light sources – the ‘markers’ – are installed at specific known locations on the tanker. A sequence of machine vision algorithms on the on-board computer of the unmanned aircraft is tasked with the processing of the images of the tanker. Specifically, detection and labeling algorithms are used to detect and identify the markers and a ‘pose estimation’ algorithm is used to estimate the relative position and orientation between the two aircraft. Detailed closed-loop simulation studies have been performed to compare the performance of two ‘pose estimation’ algorithms within a simulation environment that was specifically developed for the study of aerial refuelling problems. Special emphasis is placed on the analysis of the required computational effort as well as on the accuracy and the error propagation characteristics of the two methods. The general trade offs involved in the selection of the pose estimation algorithm are discussed. Finally, simulation results are presented and analysed.


2016 ◽  
Vol 10 (8) ◽  
pp. 798-805 ◽  
Author(s):  
Zhizhi Guo ◽  
Qianxiang Zhou ◽  
Zhongqi Liu ◽  
Chunhui Liu

2015 ◽  
Vol 63 ◽  
pp. 10-21 ◽  
Author(s):  
Claudiu Pozna ◽  
Radu-Emil Precup ◽  
Péter Földesi

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