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Mars Terrain Image Classification Using Cartesian Genetic Programming #isairas 2012

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Mars Terrain Image Classification Using Cartesian Genetic Programming #isairas 2012

  1. 1. Jürgen ’Juxi’ Leitner S. Harding, A. Förster, J. Schmidhuber istituto dalle molle di studi sull’intelligenza artificiale università della svizzera italiana idsia / usi / supsi mars terrain image classification using CGP #iSAIRAS 2012 Wednesday, September 5, 2012
  2. 2. thanks to G. Metta and IIT for this picture visual perception Wednesday, September 5, 2012
  3. 3. detecting objects Wednesday, September 5, 2012
  4. 4. learning approach Wednesday, September 5, 2012
  5. 5. INP   INP   INP   +   dilate   min   avg   cartesian genetic programming Wednesday, September 5, 2012
  6. 6. Image credit: NASA space applications Wednesday, September 5, 2012
  7. 7. Image credit: NASA space applications Wednesday, September 5, 2012
  8. 8. cgp approach Wednesday, September 5, 2012
  9. 9. INP   INP   INP   +   dilate   min   avg   cartesian genetic programming Wednesday, September 5, 2012
  10. 10. INP   INP   INP   +   dilate   min   avg   ()*+,-*" .-**/+,-*"%" .-**/+,-*"$" !" "#$" "#%" cartesian genetic 0"1/23"*)45/1" &'!" """ " programming Wednesday, September 5, 2012
  11. 11. detect Wednesday, September 5, 2012
  12. 12. detect Wednesday, September 5, 2012
  13. 13. !"#$%&$'()*'+,%-$&+*,.% •  /+0%)1#2$3%"4%)"-$.%5%677% •  /1&+8")%3+&$%5%679% •  :1)'8").%5%;<7%% •  =)>1&%'"1)&%5%?@%%A1&>1&%'"1)&5%6% •  =.,+)-%#"-$,%4"3%$B",18")% –  C<%D"3%."E%*.,+)-.% –  FB",18")+3G%.&3+&$HG%D6I<E%*)%$+'(%*.,+)-% •  J$+K%.$,$'8")%>3$..13$%+>>,*$-%4"3%$0$'18")% .>$$-% technical details Wednesday, September 5, 2012
  14. 14. detecting rocks Wednesday, September 5, 2012
  15. 15. Wednesday, September 5, 2012
  16. 16. icImage* RockDetector::runFilter() { ! icImage* node0 = InputImages[6]->gauss(3); ! icImage* node1 = node0->sqrt(); ! icImage* node9 = InputImages[5]; ! icImage* node12 = node9->unsharpen(13); ! icImage* node15 = node1->mulc(7.00936886295676); ! icImage* node24 = node15->SmoothBilateral(9); ! icImage* node31 = node24->Normalize(); ! icImage* node33 = node12->mulc(4.03286868333817); ! icImage* node35 = node33->add(node31); ! icImage* node99 = node35->SmoothBilateral(11); //cleanup ... // return ! return node99->threshold(177.2417f); } detecting rocks Wednesday, September 5, 2012
  17. 17. detecting specific rocks Wednesday, September 5, 2012
  18. 18. detectingspecificrocks Wednesday, September 5, 2012
  19. 19. classifying martian terrain Wednesday, September 5, 2012
  20. 20. martian terrain classification I.Halatci,K.Iagnemma,etal.Astudyofvisualand tactile terrain classification and classifier fusion for planetary exploration rovers. Robotica, 26(6):767– 779, 2008. C. Shang, D. Barnes, and Q. Shen. Facilitating effi- cient mars terrain image classification with fuzzy- rough feature selection. International Journal of Hybrid Intelligent Systems, 8(1):3–13, 2011. C. Shang and D. Barnes. Classification of mars mcmurdo panorama images using machine learning techniques. Acta Futura, 5:29–38, 2012. Wednesday, September 5, 2012
  21. 21. Shang et al. CGP-IP martian terrain classification I.Halatci,K.Iagnemma,etal.Astudyofvisualand tactile terrain classification and classifier fusion for planetary exploration rovers. Robotica, 26(6):767– 779, 2008. C. Shang, D. Barnes, and Q. Shen. Facilitating effi- cient mars terrain image classification with fuzzy- rough feature selection. International Journal of Hybrid Intelligent Systems, 8(1):3–13, 2011. C. Shang and D. Barnes. Classification of mars mcmurdo panorama images using machine learning techniques. Acta Futura, 5:29–38, 2012. Wednesday, September 5, 2012
  22. 22. martian terrain classification I.Halatci,K.Iagnemma,etal.Astudyofvisualand tactile terrain classification and classifier fusion for planetary exploration rovers. Robotica, 26(6):767– 779, 2008. C. Shang, D. Barnes, and Q. Shen. Facilitating effi- cient mars terrain image classification with fuzzy- rough feature selection. International Journal of Hybrid Intelligent Systems, 8(1):3–13, 2011. C. Shang and D. Barnes. Classification of mars mcmurdo panorama images using machine learning techniques. Acta Futura, 5:29–38, 2012. Wednesday, September 5, 2012
  23. 23. Shang et al. CGP-IP martian terrain classification I.Halatci,K.Iagnemma,etal.Astudyofvisualand tactile terrain classification and classifier fusion for planetary exploration rovers. Robotica, 26(6):767– 779, 2008. C. Shang, D. Barnes, and Q. Shen. Facilitating effi- cient mars terrain image classification with fuzzy- rough feature selection. International Journal of Hybrid Intelligent Systems, 8(1):3–13, 2011. C. Shang and D. Barnes. Classification of mars mcmurdo panorama images using machine learning techniques. Acta Futura, 5:29–38, 2012. Wednesday, September 5, 2012
  24. 24. collaboration if you have (labelled) data please contact us we are not martian terrain specialists :) juxi@idsia.ch http://Juxi.net/projects Wednesday, September 5, 2012
  25. 25. conclusions combining cgp with opencv creates possibilities output: executable, human-readable code for detection and identification impressive performance (and robustness) Wednesday, September 5, 2012
  26. 26. thanks for listening juxi@idsia.ch http://Juxi.net/projects further references Vincent Graziano, Tobias Glasmachers, Tom Schaul, Leo Pape, Giuseppe Cuccu,Jürgen Leitner and Jürgen Schmidhuber. Artificial Curiosity for Autonomous Space Exploration. Acta Futura, 4, pp.41-52, 2011. M. Frank, J. Leitner, M. Stollenga, S. Harding, A. Förster, and J. Schmidhuber. The modular behavioral environment for humanoids and other robots (MoBeE). In Proceedings of the International Conference on Informatics in Control, Automation and Robotics (ICINCO), 2012. S. Harding, V. Graziano, J. Leitner, J. Schmidhuber. MT-CGP: Mixed Type Cartesian Genetic Programming. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO). Philadelphia, USA. July 2012. Leitner, J., Harding, S., Förster, A., and Schmidhuber, J.. Mars Terrain Classification using Cartesian Genetic Programming. In the Proceedings of the International Symposium on AI and Robotics for Space (I-SAIRAS). 2012. S. Harding, J. Leitner, and J. Schmidhuber. Cartesian genetic programming for image processing. Book Chapter in Genetic Programming Theory and Practice X. Springer, 2012. (in print) Leitner, J., Harding, S., Frank, M., Förster, A., and Schmidhuber, J. Towards Spatial Perception: Learning to Locate Objects From Vision. In Proceedings of the Postgraduate Conference on Robotics and Development of Cognition RobotDoc, 2012. J. Leitner, S. Harding, M. Frank, A. Förster, and J. Schmidhuber. Transferring spatial perception between robots operating in a shared workspace. In Intelligent Robots and Systems, 2012. accepted. Wednesday, September 5, 2012

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