Self-Calibration of the Stereo Vision System of the Chang'e-4 Lunar Rover Based on the Points and Lines Combined Adjustment

2020 ◽  
Vol 86 (3) ◽  
pp. 169-176
Author(s):  
Shuo Zhang ◽  
Yang Jia ◽  
Song Peng ◽  
Bo Wen ◽  
Youqing Ma ◽  
...  
Keyword(s):  
Stereo Vision ◽  
Vision System ◽  
Measurement Instrument ◽  
Calibration Method ◽  
High Accuracy ◽  
Calibration Model ◽  
Lunar Rover ◽  
Self Calibration ◽  
Stereo Vision System ◽  
Laboratory Calibration

The stereo vision system is the special engineering measurement instrument of the Chang'e-4 lunar rover. It is composed of the Navigation Camera (NavCam) and the Mast Mechanism (MasMec). An improved self-calibration method for the stereo vision system of the Chang'e-4 lunar rover is proposed. The method consists of two parts: the NavCam's self-calibration and the MasMec's self-calibration. A combined adjustment based on the points and lines is proposed. The baseline constraint of the NavCam is considered. The self-calibration model of the MasMec is established based on the product-of-exponentials formula. Finally, the premission laboratory calibration and the on-site calibration are carried out. The laboratory calibration shows that the proposed approach has high accuracy. The checkpoint with a distance of about 2.7 m to the left NavCam has a point error of about 4 mm. Finally, the proposed approach is applied in the on-site calibration.

An accurate stereo vision system using cross-shaped target self-calibration method based on photogrammetry

2010 ◽  
Vol 48 (12) ◽  
pp. 1252-1261 ◽  
Author(s):  
Zhenzhong Xiao ◽  
Jin Liang ◽  
Dehong Yu ◽  
Zhengzong Tang ◽  
Anand Asundi
Keyword(s):  
Stereo Vision ◽  
Vision System ◽  
Calibration Method ◽  
Self Calibration ◽  
Stereo Vision System

A Fast Linear Calibration of Computer Stereo Vision System

2011 ◽  
Vol 305 ◽  
pp. 372-377
Author(s):  
Ke Zhang ◽  
Han Pin Luo
Keyword(s):  
Stereo Vision ◽  
Vision System ◽  
Complex Function ◽  
Calibration Method ◽  
Calibration Model ◽  
Linear Calibration ◽  
Vision Measurement ◽  
Stereo Vision System ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

Computer stereo vision has been paid high attention in areas such as industry measurement and automatic control. Calibration of stereo vision system is a key step to implement vision measurement. Nonlinear calibration method involves too many parameters and too complex function, so the processing of optimization is difficult and slow. In this paper, two digital cameras are used to set up stereo vision system which provides convenient experimental operation. The binocular stereo vision system is calibrated using linear calibration model. The results indicate that the method is stable and fast with high precision and practicability.

Binocular stereo vision system design for lunar rover

2007 ◽  
Author(s):  
Jun Chu ◽  
Chunlin Jiao ◽  
Hang Guo ◽  
Xiaoyu Zhang
Keyword(s):  
System Design ◽  
Stereo Vision ◽  
Vision System ◽  
Lunar Rover ◽  
Stereo Vision System ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

Projector calibration method based on stereo vision system

2017 ◽  
Vol 24 (6) ◽  
pp. 727-733 ◽  
Author(s):  
Shourui Yang ◽  
Miao Liu ◽  
Jiahui Song ◽  
Shibin Yin ◽  
Yin Guo ◽  
...  
Keyword(s):  
Stereo Vision ◽  
Vision System ◽  
Calibration Method ◽  
Stereo Vision System ◽  
Projector Calibration

Elastic Computing Platform Design Based on Lunar Rover Stereo Vision System

2013 ◽  
Vol 380-384 ◽  
pp. 3950-3953
Author(s):  
Zhe Wang
Keyword(s):  
Parallel Computing ◽  
Stereo Vision ◽  
Vision System ◽  
Stereo Image ◽  
Lunar Rover ◽  
Computing Platform ◽  
3D Terrain ◽  
Stereo Vision System ◽  
Elastic Computing ◽  
Image Pairs

In the second stage of Chinese lunar exploration program, lunar rover will be launched for the moon. Stereo vision system of the lunar rover is used for navigation and exploration. Binocular stereo vision cameras collect stereo image pairs of surrounding environment which are transmitted to ground station then used to reconstruct lunar 3D terrain environment. 112 image pairs are collected at one site and terrain data increases rapidly as the rover explores more unknown area so that sequential process system is difficult to generate 3D terrain environment in time. To solve this problem, an elastic parallel computing platform is designed and built using OpenMP parallel computing framework on a 16-processor shared-memory machine. In this paper, architecture of the elastic computing platform is introduced and experiments based on real terrain datasets show that the maximum speedup of the platform can reach 6.44.

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