Computer Vision on Mars |
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Authors: | Larry Matthies Mark Maimone Andrew Johnson Yang Cheng Reg Willson Carlos Villalpando Steve Goldberg Andres Huertas Andrew Stein Anelia Angelova |
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Affiliation: | (1) Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA;(2) Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA;(3) California Institute of Technology, 1200 East California Boulevard, Pasadena, CA 91125, USA |
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Abstract: | 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. |
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Keywords: | stereo vision obstacle detection visual odometry visual velocity estimation slip prediction planetary exploration |
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