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Integration of Orbital and Ground Imagery for Automation of Rover Localization

Hwangbo, Ju Won
http://rave.ohiolink.edu/etdc/view?acc_num=osu1276835399

Abstract Details

2010, Doctor of Philosophy, Ohio State University, Geodetic Science and Surveying.
Rover localization is essential to the exploration of space. The availability of sub-meter resolution satellite imagery, especially High Resolution Imaging Science Experiment (HiRISE) onboard the Mars Reconnaissance Orbiter (MRO), has opened the possibility of computing rover locations at higher accuracy by making use of detailed features seen in the satellite orbital images. This dissertation describes a new development towards automation of the rover localization process, using orbital and ground image networks. A HiRISE orbital image network on Mars is constructed based on a rigorous sensor model, bundle adjustment of HiRISE stereo images and absolute positioning using Mars Orbiter Laser Altimeter (MOLA) data. The unique HiRISE sensor configuration consists of 14 CCDs fixed to a focal plane. Due to the complexity of its sensor geometry, two technical issues need to be resolved in HiRISE stereo processing for precision topographic mapping. These technical issues are achieving coherence in the exterior orientation parameters between stereos as well as overlapping CCDs, and accurate geopositioning of HiRISE data without ground-control points. In this research, bundle adjustment strategies based on polynomial function models are applied to improve the exterior-orientation parameters. Disagreement between HiRISE CCDs is handled by the bundle adjustment, using inter-CCD tie points. HiRISE DTM was matched with MOLA DTM and points data to obtain the absolute position of the stereo model. Performance analysis of this new experiment will be given. A ground image network is also constructed using matching of Mars Exploration Rover (MER) stereo images. Rocks detected from both orbital and ground imagery serve as tie points for rover localization. From orbital images, rocks are extracted based on brightness values and the shape of dark spots. Rocks in ground images are extracted through dense stereo matching, rock peak and surface point extraction, and rock modeling. To narrow down a precise rover position, terrain matching is performed using DTMs generated from orbital and ground imagery. Finally, distribution pattern matching is implemented for rocks detected from orbital and ground imagery. The rover position is adjusted based on a 2-D affine transformation obtained from rock pattern matching. The proposed method has been tested for the Spirit rover traverse. Selection of optimal parameter values and quality control is discussed. Experimental results show that the orbital/ground rock matching approach has performed successfully for MER rover localization.
Rongxing Li (Advisor)
Alan Saalfeld (Committee Chair)
Alper Yilmaz (Committee Member)
229 p.
Engineering; Robots; Scientific Imaging; Technology
Photogrammetry; image processing; rover localization

Recommended Citations

Citations

  • Hwangbo, J. W. (2010). Integration of Orbital and Ground Imagery for Automation of Rover Localization [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1276835399

    APA Style (7th edition)

  • Hwangbo, Ju Won. Integration of Orbital and Ground Imagery for Automation of Rover Localization. 2010. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1276835399.

    MLA Style (8th edition)

  • Hwangbo, Ju Won. "Integration of Orbital and Ground Imagery for Automation of Rover Localization." Doctoral dissertation, Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1276835399

    Chicago Manual of Style (17th edition)

osu1276835399
532
© 2010, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.