Table of Content Cover Page    Full-Text Download    
Subscribe Now
Recommend the Paper
Research on Vision-based Autonomous Navigation Algorithm for RVD between Spacecrafts  
wei sun1,Long Chen2,Kai Liu3
*1, xidian university, Email : sunweitom@yahoo.com.cn
2, xidian university, Email : poulo214@hotmail.com
3, tsinghua university, Email : liukai.v@gmail.com
 
Abstract .In order to solve the autonomous navigation problem of RVD(Rendezvous and Docking) in near distance (<2m) for the on-orbit service of spacecraft, a vision-guided method based on geometry feature of the spacecraft was proposed to measure the relative pose (position and attitude) between two spacecrafts. Firstly, after smoothing the captured image, edge image was obtained by using fast self-adaptive edge detection. We use the line feature to segment the interesting area of the spacecraft and the geometry feature was used to recognize the interesting areas, and the intersection points of the object were gotten. Secondly, the coordinates of these points in the world coordinate were figured out by the proposed fast stereo matching algorithm and 3D reconstruction technical. Based on these coordinates, the pose with respect to the world coordinate was calculated. Finally, lines of the recognized region were extracted and tracked based on Hough transform. In order to verify the effectiveness of the proposed algorithm, a hardware system was established based on high performance DSP. The results of satellite model experiment demonstrate that the relative position errors are less than ±20mm, relative attitude errors are less than ±2°, and measuring speed is up to 8fps which satisfies the precision and speed requirement of the RVD system. The errors in this measurement system were analyzed.
 
Keywords : Autonomous navigation;RVD;Object recognition;Optical measurement;Binocular stereo vision
 URL: http://dx.doi.org/10.7321/jscse.v2.n5.1  
 
 

Subscribe Now

Email :    
Subscribe to receive free TOC's JSCSE by email
Subscribe

Recommend To Friend

Email :     People