Skip to main content Accessibility help
×
Home

The Cyborg Astrobiologist: testing a novelty detection algorithm on two mobile exploration systems at Rivas Vaciamadrid in Spain and at the Mars Desert Research Station in Utah

  • P.C. McGuire (a1) (a2) (a3), C. Gross (a1), L. Wendt (a1), A. Bonnici (a4), V. Souza-Egipsy (a2), J. Ormö (a2), E. Díaz-Martínez (a2), B.H. Foing (a5), R. Bose (a3), S. Walter (a1), M. Oesker (a6), J. Ontrup (a6), R. Haschke (a6) and H. Ritter (a6)...

Abstract

In previous work, a platform was developed for testing computer-vision algorithms for robotic planetary exploration. This platform consisted of a digital video camera connected to a wearable computer for real-time processing of images at geological and astrobiological field sites. The real-time processing included image segmentation and the generation of interest points based upon uncommonness in the segmentation maps. Also in previous work, this platform for testing computer-vision algorithms has been ported to a more ergonomic alternative platform, consisting of a phone camera connected via the Global System for Mobile Communications (GSM) network to a remote-server computer. The wearable-computer platform has been tested at geological and astrobiological field sites in Spain (Rivas Vaciamadrid and Riba de Santiuste), and the phone camera has been tested at a geological field site in Malta. In this work, we (i) apply a Hopfield neural-network algorithm for novelty detection based upon colour, (ii) integrate a field-capable digital microscope on the wearable computer platform, (iii) test this novelty detection with the digital microscope at Rivas Vaciamadrid, (iv) develop a Bluetooth communication mode for the phone-camera platform, in order to allow access to a mobile processing computer at the field sites, and (v) test the novelty detection on the Bluetooth-enabled phone camera connected to a netbook computer at the Mars Desert Research Station in Utah. This systems engineering and field testing have together allowed us to develop a real-time computer-vision system that is capable, for example, of identifying lichens as novel within a series of images acquired in semi-arid desert environments. We acquired sequences of images of geologic outcrops in Utah and Spain consisting of various rock types and colours to test this algorithm. The algorithm robustly recognized previously observed units by their colour, while requiring only a single image or a few images to learn colours as familiar, demonstrating its fast learning capability.

Copyright

References

Hide All
Aha, D.W., Kibler, D. & Albert, M.K. (1991). Mach. Learn. 6(1), 3766.
Alexander, D.A. et al. (2006). J. Geophys. Res. 111, E02S02.
Barnes, D. et al. (2006). Int. J. Astrobiol. 5, 221241.
Bartolo, A. et al. (2007). Int. J. Astrobiol., 6, 255261, http://arxiv.org/abs/0707.0808v1.
Bilbey, S.A. (1998). Modern Geology. 22, 87120.
Bogacz, R., Brown, M.W. & Giraud-Carrier, C. (1999). High capacity neural networks for familiarity discrimination. In Proc. Artificial Neural Networks. ICANN 99. Ninth International Conference on (Conf. Publ. No. 470), vol. 2, pp. 773778.
Bogacz, R., Brown, M.W. & Giraud-Carrier, C. (2001). J. Comput. Neurosci. 10(1), 523.
Borg, J.C., Camilleri, K.P. & Farrugia, P.J. (2003). Innovative Early Stage Design Product Prototyping (InPro), http://www.eng.um.edu.mt/~inpro.
Calvo, J.P., Alonso, A.M. & Garcia del Cura, A.M. (1989). Paleogeography, Paleoclimate Paleoecology, 70, 199214.
Castano, R. et al. (2007). Onboard Autonomous Rover Science. In Proc. IEEE Aerospace Conf., Big Sky, MT.
Castilla Cañamero, G. (2001). Informe sobre las prácticas profesionales realizadas en el Centro de Educación Ambiental: El Campillo. Internal report to the Consejería de Medio Ambiente de la Comunidad de Madrird.
Chen, Y. & Wang, J.Z. (2004). J. Mach. Learn. Res. 5, 913939.
Dubowsky, S., Iagnemma, K., Liberatore, S., Lambeth, D., Plante, J.S. & Boston, P.A. (2005). Concept mission: microbots for large-scale planetary surface and subsurface exploration. In Proc.s of the 2005 Space Technology and Applications International Forum (STAIF), vol. 746, pp. 14491458.
Farrugia, P.J., Borg, J.C., Camilleri, K.P., Spiteri, C. & Bartolo, A. (2004). A cameraphone-based approach for the generation of 3{D} models from paper sketches. In Proc. Eurographics 2004 Workshop on Sketch-based Interfaces and Modeling, pp. 3242.
Fink, W., Dohm, J.M., Tarbell, M.A., Hare, T.M. & Baker, V.R. (2005). Planet. Space Sci. 53, 14191426.
Foing, B.H. et al. (2009a). Validation of instruments and robotics from EuroGeoMars & Moon Campaign. In Proc. European Planetary Science Congress (EPSC), Potsdam, Germany, extended abstract 643.
Foing, B.H. et al. (2009b). ExoGeoLab lander/rover instruments and EuroGeoMars MDRS campaign. In Proc. Lunar and Planetary Science Conf. (LPSC), The Woodlands, Texas, extended abstract 2567.
Foing, B.H. et al. (2009c). Daily reports from MDRS (crew 76 and 77), http://desert.marssociety.org/mdrs/fs08/.
Freixenet, J., Munoz, X., Marti, J. & Lladó, X. (2004). Color texture segmentation by region-boundary cooperation. In Proc. Computer Vision-ECCV 2004, Eighth European Conf. on Computer Vision, Prague, Czech Republic, (Part II, Lecture Notes in Computer Science), ed. Pajdla, T. & Matas, J., vol. 3022, pp. 250261. Springer, also available in the CVonline archive: http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/FREIXENET1/eccv04.html.
Gentner, D. & Namy, L.L. (2006). Curr. Dir. Psychol. Sci. 15(6), 297301.
Griffiths, A.D., Coates, A.J., Jaumann, R., Michaelis, H., Paar, G., Barnes, D., Josset, J.-L. & the PanCam Team (2006). Int. J. Astrobiol. 5, 269275.
Gross, C. et al. (2009). Testing the Cyborg Astrobiologist at the Mars Desert Research Station (MDRS), Utah. In Proc. European Planetary Science Congress (EPSC), Potsdam, Germany, extended abstract 548.
Gulick, V.C., Hart, S.D., Shi, X. & Siegel, V.L. (2004). Developing an automated science analysis system for Mars surface exploration for MSL and beyond. In Proc. Lunar and Planetary Institute Conf. XXXV, extended abstract #2121.
Gulick, V.C., Morris, R.L., Ruzon, M.A. & Roush, T.L. (2001). J. Geophys. Res. 106, 77457764.
Halatci, I, Brooks, C.A. & Iagnemma, K. (2007). Terrain classification and classifier fusion for planetary exploration rovers. In Proc. IEEE Aerospace Conference, Big Sky, MT, pp. 111.
Halatci, I., Brooks, C.A. & Iagnemma, K. (2008). Robotica 26, 767779.
Haralick, R.M., Shanmugam, K. & Dinstein, I. (1973). IEEE Trans. Systems Man and Cybernetics. 3, 610621.
IGME (Instituto Geológico y Minero de España). (1975). Mapa geológico de España E 1:50,000, Arganda (segunda serie, primera edicion), Hoja numero 583, Memoria explicativa, pp. 325.
Itti, L, Koch, C. & Niebur, E. (1998). IEEE Trans. Pattern Anal. Mach. Intell. 20(11), 12541259.
King, D.T. Jr. & Petruny, L.W. (2008). Impact spherule-bearing, Cretaceous-Tertiary boundary sand body, Shell Creek stratigraphic section, Alabama, USA. In The Sedimentary Record of Impacts, ed. Evans, K.R., Horton, J.W. Jr., King, D.T. Jr. & Morrow, J.R. Special Paper 437, pp. 179187. Geological Society of America, Boulder, CO.
Kjemperud, A.V, Schomacker, E.R. & Cross, T.A. (2008). AAPG Bull. 92, 10551076.
Maron, O. & Lozano-Perez, T. (1998). A framework for multiple-instance learning. In Proc. of the 1998 Conf. on Advances in Neural Information Processing Systems (NIPS), vol. 10, pp. 570576. MIT Press.
Matthies, L. et al. (2007). Int. J. Comput. Vis. 75(1), 6792.
McGreevy, M.W. (1992). Presence 1(4), 375403.
McGreevy, M.W. (1994). An ethnographic object-oriented analysis of explorer presence in a volcanic terrain environment, NASA Technical Memorandum #108823, Ames Research Center, Moffett field, California.
McGuire, P.C., Fritsch, J., Steil, J.J., Roethling, F., Fink, G.A., Wachsmuth, S., Sagerer, G. & Ritter, H. (2002). Multi-Modal human-machine communication for instructing robot grasping tasks. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Lausanne, Switzerland, pp. 10821089. IEEE publications.
McGuire, P.C., Ormö, J.O., Díaz-Martínez, E., Rodríguez-Manfredi, J.A., Gómez-Elvira, J., Ritter, H., Oesker, M. & Ontrup, J. (2004a). Int. J. Astrobiol. 3, 189207, http://arxiv.org/abs/cs.CV/0410071.
McGuire, P.C. et al. (2004b). Cyborg systems as platforms for computer-vision algorithm-development for astrobiology. In Proc. of the III European Workshop on Exo-Astrobiology; Mars: The Search for Life, Centro de Astrobiologia, Madrid, ESA SP- 545, pp. 141144. http://arxiv.org/abs/cs.CV/0401004.
McGuire, P.C. et al. (2005). Int. J. Astrobiol. 4, 101113, http://arxiv.org/abs/cs.CV/0505058.
Ontrup, J., Ehnert, N., Bergmann, M. & Nattkemper, T.W. (2009). Biigle – Web 2.0 enabled labeling and exploring of images from the Arctic deep-sea observatory HAUSGARTEN. In Proc. OCEANS′09 IEEE Bremen. Balancing technology with future needs, abstract.
Purser, A., Bergmann, M., Lundälv, T., Ontrup, J. & Nattkemper, T.W. (2009, in press). Use of machine-learning algorithms for the automated detection of cold-water coral habitats—a pilot study. Mar. Ecol. Progr. doi:10.3354/meps08154.
Rae, R., Fislage, M. & Ritter, H. (1999). KI-Künstliche Intelligenz, Themenheft Aktive Sehsysteme 01, 1824, March issue, Hrsg. Bärbel Mertsching.
Read, S.J. (1983). J. Pers. Soc. Psychol. 45(2), 323334.
Ritter, H., Steil, J.J., Noelker, C., Roethling, F. & McGuire, P. (2003). Rev. Neurosci. 14, 121143.
Ritter, H. et al. (1992, 2002). The Graphical Simulation Tookit, Neo/NST, for more details about the {NEO} project, see: http://ni.www.techfak.uni-bielefeld.de/neo/.
Sebe, N., Tian, Q., Loupias, E., Lew, M. & Huang, T.S. (2003). Image Vis. Comput. Special Issue on Machine Vision, 21, 10871095.
Squyres, S.W. et al. (2004a). Science 305, 794799.
Squyres, S.W. et al. (2004b). Science 306, 16981703.
Turner, C.E. & Fishman, N.S. (1991). Geol. Soc. Am. Bull. 103, 538558.
Volpe, R. (2003). Rover functional autonomy development for the Mars Mobile Science Laboratory. In Proc. IEEE Aerospace Conf., Big Sky, MT, vol. 2, pp. 2_6432_652.
Wendt, L. et al. (2009). The Cyborg Astrobiologist: teaching computers to find uncommon or novel areas of geological scenery in real-time. In Proc. European Space Agency International Conf. on Comparative Planetology: Venus – Earth – Mars, ESTEC, Noordwijk, The Netherlands, extended abstract.
Yim, M., Shirmohammadi, B. & Benelli, D. (2007). Amphibious modular robotic astrobiology. In Proc. Unmanned Systems Technology IX, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, vol. 6561, p. 65611S.
Zhang, Q. & Goldman, S.A. (2002). EM-DD: An improved multiple-instance learning technique. In Proc. of the 2002 Conf. on Advances in Neural Information Processing Systems (NIPS), vol. 14, pp. 10731080. MIT Press.

Keywords

The Cyborg Astrobiologist: testing a novelty detection algorithm on two mobile exploration systems at Rivas Vaciamadrid in Spain and at the Mars Desert Research Station in Utah

  • P.C. McGuire (a1) (a2) (a3), C. Gross (a1), L. Wendt (a1), A. Bonnici (a4), V. Souza-Egipsy (a2), J. Ormö (a2), E. Díaz-Martínez (a2), B.H. Foing (a5), R. Bose (a3), S. Walter (a1), M. Oesker (a6), J. Ontrup (a6), R. Haschke (a6) and H. Ritter (a6)...

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed