Research on Automatic Assembling Method of Large Parts of Spacecraft Based on Vision Guidance

2021 ◽  
Author(s):  
Zhang Man ◽  
Zhang Chengcheng ◽  
Wang Wei ◽  
Du Ruizhao ◽  
Meng Shaohua
Keyword(s):  
1995 ◽  
Vol 2 (1) ◽  
pp. 65-76 ◽  
Author(s):  
J. Billingsley ◽  
M. Schoenfisch

2013 ◽  
Vol 117 (1197) ◽  
pp. 1075-1101 ◽  
Author(s):  
S. M. Parkes ◽  
I. Martin ◽  
M. N. Dunstan ◽  
N. Rowell ◽  
O. Dubois-Matra ◽  
...  

Abstract The use of machine vision to guide robotic spacecraft is being considered for a wide range of missions, such as planetary approach and landing, asteroid and small body sampling operations and in-orbit rendezvous and docking. Numerical simulation plays an essential role in the development and testing of such systems, which in the context of vision-guidance means that realistic sequences of navigation images are required, together with knowledge of the ground-truth camera motion. Computer generated imagery (CGI) offers a variety of benefits over real images, such as availability, cost, flexibility and knowledge of the ground truth camera motion to high precision. However, standard CGI methods developed for terrestrial applications lack the realism, fidelity and performance required for engineering simulations. In this paper, we present the results of our ongoing work to develop a suitable CGI-based test environment for spacecraft vision guidance systems. We focus on the various issues involved with image simulation, including the selection of standard CGI techniques and the adaptations required for use in space applications. We also describe our approach to integration with high-fidelity end-to-end mission simulators, and summarise a variety of European Space Agency research and development projects that used our test environment.


Author(s):  
Tao Zhang ◽  
Dejun Li ◽  
Mingwei Lin ◽  
Tianlei Wang ◽  
Canjun Yang
Keyword(s):  

2021 ◽  
Author(s):  
Qimeng Huang ◽  
Yanhua Shao ◽  
Yanying Mei ◽  
Zhiyuan Chang ◽  
Liangtao Zhong ◽  
...  

2019 ◽  
Vol 9 (19) ◽  
pp. 4108 ◽  
Author(s):  
Wu ◽  
Sun ◽  
Zou ◽  
Xiao ◽  
Zhai

Applying computer vision to mobile robot navigation has been studied more than twodecades. The most challenging problems for a vision-based AGV running in a complex workspaceinvolve the non-uniform illumination, sight-line occlusion or stripe damage, which inevitably resultin incomplete or deformed path images as well as many fake artifacts. Neither the fixed thresholdmethods nor the iterative optimal threshold methods can obtain a suitable threshold for the pathimages acquired on all conditions. It is still an open question to estimate the model parameters ofguide paths accurately by distinguishing the actual path pixels from the under- or oversegmentationerror points. Hence, an intelligent path recognition approach based on KPCA–BPNNand IPSO–BTGWP is proposed here, in order to resist the interferences from the complexworkspace. Firstly, curvilinear paths were recognized from their straight counterparts by means of apath classifier based on KPCA–BPNN. Secondly, an approximation method based on BTGWP wasdeveloped for replacing the curve with a series of piecewise lines (a polyline path). Thirdly, a robustpath estimation method based on IPSO was proposed to figure out the path parameters from a set ofpath pixels surrounded by noise points. Experimental results showed that our approach caneffectively improve the accuracy and reliability of a low-cost vision-guidance system for AGVs in acomplex workspace.


Author(s):  
Giampiero Campa ◽  
Mario Luca Fravolini ◽  
Antonio Ficola ◽  
Marcello Napolitano ◽  
Brad Seanor ◽  
...  

2017 ◽  
Vol 887 ◽  
pp. 012093
Author(s):  
Tongqing Feng ◽  
Bin Jiao

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