Autonomous Science For Future Planetary Exploration Operations

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Type

Student thesis: Doctoral ThesisDoctor of Philosophy

Original languageEnglish
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Thesis sponsors
  • Engineering & Physical Sciences Research Council
Award date08 Jun 2010
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Abstract

A major mission driver for space exploration is to maximise science data return whilst minimising ground-based human intervention and hence associated operations costs. Future robotic exploration such as the ESA ExoMars mission (launch 2018), and the eventual Mars Sample Return (MSR) mission will require rovers to travel further and faster than has been achieved to date. In order to make this possible it is essential that currently earth bound decisions be transferred to the exploration platform wherever possible. In line with this, this Thesis presents a new solution which requires a combined on-Earth and on-board rover approach. The on-board element utilises autonomy and basic image processing techniques to image a predefined number of potential targets. The Earth-based element uses a more complex knowledge based system approach which has been primed by a human Planetary Geology Expert. This Earth based approach, which is used to process the autonomously captured images, is presented as a precursor to a future onboard solution. Both solution elements represent significant advances in the current state of the art. This Thesis provides details of the design, implementation and experimentation undertaken to validate the performance of both the on-board and on-Earth solution elements.