Seeking Scent with Robotics for Planetary Exploration

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  • This thesis presents the work towards analyzing the odour source localization problem found in nature as a suitable analogy for planetary exploration missions. The contributions are models of two environments for which the analogy may be relevant, the training of a recurrent neural network that replicates simple forms of odour source locational strategies found in nature, and the analysis and advancement of a source likelihood map algorithm for predicting the location of a chemical source given individual detection events.Two missions that may be suitable for using the odour source localization analogy are locating methane sources on Mars and choosing a landing site for exploration of Enceladus' postulated subsurface ocean. The details in training recurrent neural networks for simple moth behaviours is shown and the results using the dynamic Mars methane plumes are discussed. The advancement of a binary chemical detection and source-localization method is shown, which improves accuracy.

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  • Copyright © 2013 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
Date Created
  • 2013


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