This thesis deals with the challenge of autonomous navigation of the ExoMars rover.
The absence of global positioning systems (GPS) in space, added to the limitations
of wheel odometry makes autonomous navigation based on these two techniques - as
done in the literature - an inviable solution and necessitates the use of other approaches.
That, among other reasons, motivates this work to use solely visual data to solve the
robot’s Egomotion problem.
The homogeneity of Mars’ terrain makes the robustness of the low level image
processing technique a critical requirement. In the first part of the thesis, novel solutions
are presented to tackle this specific problem. Detection of robust features against
illumination changes and unique matching and association of features is a sought after
capability. A solution for robustness of features against illumination variation is proposed
combining Harris corner detection together with moment image representation.
Whereas the first provides a technique for efficient feature detection, the moment images
add the necessary brightness invariance. Moreover, a bucketing strategy is used
to guarantee that features are homogeneously distributed within the images. Then, the
addition of local feature descriptors guarantees the unique identification of image cues.
In the second part, reliable and precise motion estimation for the Mars’s robot is
studied. A number of successful approaches are thoroughly analysed. Visual Simultaneous
Localisation And Mapping (VSLAM) is investigated, proposing enhancements
and integrating it with the robust feature methodology. Then, linear and nonlinear optimisation
techniques are explored. Alternative photogrammetry reprojection concepts
are tested. Lastly, data fusion techniques are proposed to deal with the integration of
multiple stereo view data.
Our robust visual scheme allows good feature repeatability. Because of this,
dimensionality reduction of the feature data can be used without compromising the
overall performance of the proposed solutions for motion estimation. Also, the developed
Egomotion techniques have been extensively validated using both simulated and
real data collected at ESA-ESTEC facilities. Multiple stereo view solutions for robot
motion estimation are introduced, presenting interesting benefits. The obtained results
prove the innovative methods presented here to be accurate and reliable approaches
capable to solve the Egomotion problem in a Mars environment. / © Cranfield University
| Identifer | oai:union.ndltd.org:CRANFIELD1/oai:dspace.lib.cranfield.ac.uk:1826/8036 |
| Date | 08 October 2013 |
| Creators | Bartolome, D R |
| Contributors | Aouf, N |
| Source Sets | CRANFIELD1 |
| Detected Language | English |
| Type | Thesis or dissertation, Doctoral, PhD |
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