Robotics and Autonomous Systems
Extracting rocks from mars images with data fields
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I
Three-dimensional SLAM for mapping planetary work site environments
Journal of Field Robotics
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This paper introduces the concept and design of a new integrated approach to long-range autonomous Mars rover localization based on the incremental bundle adjustment and visual odometry technologies that have been individually experimented with during the 2003 Mars Exploration Rover mission. The design result indicates that a rover would have a varying performance in traversing from 7.5 to 118 m within one traverse leg under various scenarios including camera systems and traverse geometry, while maintaining the onboard rover localization accuracy at 1%. To implement the proposed integrated approach, the key is to develop autonomous cross-site tie point selection algorithms for automatic generation of a sufficient number of high quality tie points to link all the images and to form the image network. New methods of rock extraction, rock modeling, and rock matching from multiple rover sites are developed to automate cross-site tie point selection. Rocks are extracted from three-dimensional ground points generated by stereo image matching, and then modeled using analytical surfaces such as hemispheroid, semiellipsoid, cone, and tetrahedron. Rocks extracted and modeled from two rover sites are matched by a combination of rock model matching and rock distribution pattern matching. The matched rocks are used as cross-site tie points for a subsequent bundle adjustment. The presented results show that the proposed cross-site tie point selection approach functions successfully for medium-range (up to 26 m) traverse legs. © 2007 Wiley Periodicals, Inc.