Computer vision on Mars

被引:140
作者
Matthies, Larry
Maimone, Mark
Johnson, Andrew
Cheng, Yang
Willson, Reg
Villalpando, Carlos
Goldberg, Steve
Huertas, Andres
Stein, Andrew
Angelova, Anelia
机构
[1] CALTECH, Jet Prop Lab, Pasadena, CA 91109 USA
[2] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
[3] CALTECH, Pasadena, CA 91125 USA
关键词
stereo vision; obstacle detection; visual odometry; visual velocity estimation; slip prediction; planetary exploration;
D O I
10.1007/s11263-007-0046-z
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Increasing the level of spacecraft autonomy is essential for broadening the reach of solar system exploration. Computer vision has and will continue to play an important role in increasing autonomy of both spacecraft and Earth-based robotic vehicles. This article addresses progress on computer vision for planetary rovers and landers and has four main parts. First, we review major milestones in the development of computer vision for robotic vehicles over the last four decades. Since research on applications for Earth and space has often been closely intertwined, the review includes elements of both. Second, we summarize the design and performance of computer vision algorithms used on Mars in the NASA/JPL Mars Exploration Rover (MER) mission, which was a major step forward in the use of computer vision in space. These algorithms did stereo vision and visual odometry for rover navigation and feature tracking for horizontal velocity estimation for the landers. Third, we summarize ongoing research to improve vision systems for planetary rovers, which includes various aspects of noise reduction, FPGA implementation, and vision-based slip perception. Finally, we briefly survey other opportunities for computer vision to impact rovers, landers, and orbiters in future solar system exploration missions.
引用
收藏
页码:67 / 92
页数:26
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