Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-14T07:26:50.716Z Has data issue: false hasContentIssue false
  • English
  • Français

Martian methane plume models for defining Mars rover methane source search strategies

Published online by Cambridge University Press:  19 February 2018

Christopher Nicol ,
Alex Ellery ,
Brian Lynch ,
Ed Cloutis  and
Guido de Croon
Christopher Nicol
Affiliation:
Department of Mechanical & Aerospace Engineering, Carleton University, Ottawa, ON, Canada
Alex Ellery*
Affiliation:
Department of Mechanical & Aerospace Engineering, Carleton University, Ottawa, ON, Canada
Brian Lynch
Affiliation:
Department of Mechanical & Aerospace Engineering, Carleton University, Ottawa, ON, Canada
Ed Cloutis
Affiliation:
Department of Geography, University of Winnipeg, Winnipeg, MB, Canada
Guido de Croon
Affiliation:
Advanced Concepts Team, European Space Agency (ESTEC), Noordwijk, Netherlands
*
Author for correspondence: Alex Ellery, [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

The detection of atmospheric methane on Mars implies an active methane source. This introduces the possibility of a biotic source with the implied need to determine whether the methane is indeed biotic in nature or geologically generated. There is a clear need for robotic algorithms which are capable of manoeuvring a rover through a methane plume on Mars to locate its source. We explore aspects of Mars methane plume modelling to reveal complex dynamics characterized by advection and diffusion. A statistical analysis of the plume model has been performed and compared to analyses of terrestrial plume models. Finally, we consider a robotic search strategy to find a methane plume source. We find that gradient-based techniques are ineffective, but that more sophisticated model-based search strategies are unlikely to be available in near-term rover missions.

Keywords

Chemical source localizationgradient-descent algorithmsMars methaneplume dynamicssource localization
Type
Research Article
Information
International Journal of Astrobiology , Volume 17 , Special Issue 3: Robotic Astrobiology , July 2018 , pp. 228 - 238
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Atreya, S, Mahaffy, P and Wong, A-S (2007) Methane and related trace species on Mars; origin, loss, implications for life and habitability. Planetary & Space Science 55, 358–369.CrossRefGoogle Scholar
Braitenberg, V (1984) Vehicles: Experiments in Synthetic Psychology. Boston, MA: MIT Press.Google Scholar
Castro, R and Sauer, T (1997) Chaotic stochastic resonance: noise-enhanced reconstruction of attractors. Physical Review Letters 79(6), 1030–1033.CrossRefGoogle Scholar
Chassefi`ere, E (2009) Metastable methane clathrate particles as a source of methane to the Martian atmosphere. Icarus 204(1), 137–144.Google Scholar
Chastain, B and Chevrier, V (2007) Methane clathrate hydrates as a potential source for Martian atmospheric methane. Planetary & Space Science 55, 1246–1256.CrossRefGoogle Scholar
Chatwin, P (1982) The use of statistics in describing and predicting the effects of dispersing gas clouds. Journal of Hazardous Materials 6, 213–230.Google Scholar
Coombes, S (2005) Waves, bumps and patterns in neural field theories. Biological Cybernetics 93, 91–108.Google Scholar
Cross, M, Ellery, A and Qadi, A (2013) Estimating terrain parameters for a rigid wheel rover using neural networks. Journal of Terramechanics 50(3), 165–174.Google Scholar
de Croon, G, O'Connor, L, Nicol, C and Izzo, D (2013) Evolutionary approach to odour source localization. Neurocomputing 121, 461–497.Google Scholar
Ellery, A, Nicol, C and Cloutis, E (2012) Scent of Science: Model Creation for Odour Based Control of Robotic Vehicles. ESA Advanced Concepts Team Report 11-6301.Google Scholar
Farkas, S and Shorey, H (1972) Chemical trail-following by flying insects: a mechanism for orientation to a distant odour source. Science 178, 67–68.Google Scholar
Farrell, J, Murlis, J, Long, X, Li, W and Ring, T (2002) Filament-based atmospheric dispersion model to achieve short time-scale structure of odour plumes. Environmental Fluid Mechanics 2, 143–169.Google Scholar
Farrell, J, Pang, S and Li, W (2003) Plume mapping via hidden Markov methods. IEEE Trans Systems Man & Cybernetics B: Cybernetics 33(6), 850–863.Google Scholar
Farrell, W, Delory, G and Atreya, S (2006) Martian dust storms as a possible sink of atmospheric methane. Geophysical Research Letters 33(21), 2–5.CrossRefGoogle Scholar
Fielding, J and Underwood, C (2004) MASSIVA: Mars surface sampling and imaging VTOL aircraft. Journal of British Interplanetary Society 57, 306–312.Google Scholar
Formisano, V, Atreya, S, Encrenaz, T, Ignatiev, N and Giuranna, M (2004) Detection of methane in the atmosphere of Mars. Science 306, 1758–1761.CrossRefGoogle ScholarPubMed
Gallant, M, Ellery, A and Marshall, J (2013) Rover-based autonomous science by probabilistic identification and evaluation. Journal of Intelligent & Robotic Systems 72(3), 591–613.Google Scholar
Grasso, F, Consi, T, Mountain, D and Atema, J (2000) Biomimetic robot lobster performs chemo-orientation in turbulence using a pair of spatially separated sensors: progress and challenges. Robotics & Autonomous Systems 30(1–2), 115–131.Google Scholar
Hewitt, R, Ellery, A and de Ruiter, A (2017) Training a terrain traversibility classifier for a planetary rover through simulation. International Journal of Advanced Robotic Systems 14(5), 1–14.Google Scholar
Hoffman, M, Greybush, S, Wilson, J, Gyarmati, G, Hiffman, R, Kalnay, E, Ide, K, Kostelich, E, Miyoshi, T and Szunyogh, I (2010) Ensemble Kalman filter data assimilation system for the Martian atmosphere: implementation and simulation experiments. Icarus 209(2), 470–481.CrossRefGoogle Scholar
Ishida, H, Nakamoto, T and Moriizumi, T (1998) Remote sensing of gas/odor source location and concentration distribution using mobile system. Sensors and Actuators B: Chemical 49, 52–57.Google Scholar
Itti, L, Koch, C and Niebur, E (1996) Model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis & Machine Intelligence 20(11), 1254–1259.Google Scholar
Jones, C (1983) On the structure of instantaneous plumes in the atmosphere. Journal of Hazardous Materials 7, 87–112.Google Scholar
Kerguelen, V and Card, R (1996) Reinforcement mechanisms of olfactory conditioning during parasitisation by the parasitoid Brachymeria intermedia. Journal of Insect Behaviour 9(6), 947–960.Google Scholar
Kowaldo, G and Russell, R (2006) Using naive physics for odour localization in a cluttered indoor environment. Autonomous Robots 20(3), 215–230.Google Scholar
Krasnopolsky, V, Maillard, J and Owen, T (2004) Detection of methane in the Martian atmosphere: evidence for life? Icarus 172(2), 537–547.Google Scholar
Lef`evre, F and Forget, F (2009) Observed variations of methane on Mars unexplained by known atmospheric chemistry and physics. Nature 460, 720–723.Google Scholar
Lumley, J and Panofsky, H (1964) The Structure of Atmospheric Turbulence. New York: Interscience Publishers.Google Scholar
Mafra-Neto, A and Carde, R (1994) Fine-scale structure of pheromone plumes modulates upwind orientation of flying moths. Nature 369, 142–144.CrossRefGoogle Scholar
Mahaffy, P, Webster, C, Atreya, S, Franz, H, Wong, M, Conrad, P, Harpold, D, Jones, J, Leshin, L, Manning, H, Owen, T, Pepin, R, Squyres, S and Trainer, M, MSL Science Team (2013) Abundance and isotopic composition of gases in the Martian atmosphere from the Curiosity rover. Science 341, 263–266.Google Scholar
Mischna, M, Allen, M, Richardson, M, Newman, C and Toigo, A (2011) Atmospheric modeling of Mars methane surface releases. Planetary & Space Science 59(2–3), 227–237.CrossRefGoogle Scholar
Mitaim, S and Kosko, B (1998) Adaptive stochastic resonance. Proceedings of the IEEE 86(11), 2152–2183.Google Scholar
Mumma, M, Villanueva, G, Novak, R, Hewagama, T, Bonev, B, DiSanti, M, Mandell, A and Smith, M (2009) Strong release of methane on Mars in northern summer 2003. Science 323, 1041–1045.Google Scholar
Munterer, O (2010) Serpentine and serpentinization: a link between planet formation and life. Geology 38(10), 959–960.Google Scholar
Murlis, J, Elkinton, J and Carde, R (1992) Odour plumes and how insects use them. Annual Review of Entomology 37, 505–532.Google Scholar
Nevitt, G (1999) Olfactory foraging in Antarctic seabirds: a species-specific attraction to krill odours. Marine Ecology Progress Series 177, 235–241.CrossRefGoogle Scholar
Olsen, K, Cloutis, E and Strong, K (2012) Small-scale methane dispersion modelling for possible plume sources on the surface of Mars. Geophysical Research Letters 39, 1–5. doi: 10.1029/2012GL052922.Google Scholar
Pang, S and Farrell, J (2006) Chemical plume source localisation. IEEE Transactions on Systems Man & Cybernetics B: Cybernetics 36(5), 1068–1080.Google Scholar
Parnell, J, Boyce, A and Blamey, N (2010) Follow the methane: the search for a deep biosphere and the case for sampling serpentinites on Mars. International Journal of Astrobiology 9(4), 193–200.Google Scholar
Qai, A, Cloutis, E, Samson, C, Whyte, L, Ellery, A, Bell, J, Berard, G, Bovin, A, Haddad, E, Lavoie, J, Jamroz, W, Kruzelecky, R, Mack, A, Olsen, K, Perrot, M, Popa, D, Rhind, T, Sharma, R, Stromberg, J, Strong, K, Tremblay, A, Wilhelm, R, Wing, B and Wong, B (2015) Mars methane analogue mission: mission simulation and rover operations at Jeffrey mine and Norbestos mine, Quebec, Canada. Advances in Space Research 55(10), 2414–2426.Google Scholar
Schmidhuber, J (2015) Deep learning in neural networks: an overview. Neural Networks 61, 85–117.Google Scholar
Sutton, O (1953) Micrometeorology. New York: McGraw-Hill Publishers.Google Scholar
Vergassola, M, Villermaux, E and Shraiman, B (2007) Infotaxis as a strategy for searching without gradients. Nature 445, 406–409.CrossRefGoogle ScholarPubMed
Viscardy, S, Daerden, F and Neary, L (2016) Formation of layers of methane in the atmosphere of Mars after surface release. Geophysical Research Letters 43(5), 1868–1875. doi: 10.1002/2015FL067443.CrossRefGoogle Scholar
Wan, E and van der Merwe, R (2000) Unscented Kalman filter for nonlinear estimation. IEEE International Symposium on Adaptive Systems for Signal Processing, Communications & Control, paper no. 882463.Google Scholar
Webster, C and Mahaffy, P (2011) Determining the local abundance of Martian methane and its 13C/12C and D/H isotopic ratios for comparison with related gas and soil analysis on the 2011 Mars Science Laboratory (MSL) mission. Planetary & Space Science 59(2–3), 271–283.Google Scholar
Webster, C, Mahaffy, P, Fkesch, G, Niles, P, Jones, J, Leshin, L, Atreya, S, Stern, J, Christensen, L, Owen, T, Franz, H, Pepin, R and Steele, A, MSL Science Team (2013) Isotopic ratios of H, C and O in CO2 and H2O of the Martian atmosphere. Science 341, 260–263.Google Scholar
White, F (1998) Fluid Mechanics. 4th edn. New York: McGraw-Hill Higher Education.Google Scholar
Zahnle, K, Freedman, R and Catling, D (2011) Is there methane on Mars? Icarus 212(2), 493–503.CrossRefGoogle Scholar
Zwiebel, L and Takken, W (2004) Olfactory regulation of mosquito-host interactions. Insect Biochemistry & Molecular Biology 34(7), 645–652.Google Scholar