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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
thanks to G. Metta and IIT for this picture




                                                   visual
                                              perception




Wednesday, September 5, 2012
detecting
            objects
Wednesday, September 5, 2012
learning
                               approach




Wednesday, September 5, 2012
INP               INP     INP     +      dilate     min     avg  




                                                         cartesian
                                                           genetic
                                                     programming
Wednesday, September 5, 2012
Image credit: NASA




              space
        applications
Wednesday, September 5, 2012
Image credit: NASA




              space
        applications
Wednesday, September 5, 2012
cgp
             approach
Wednesday, September 5, 2012
INP               INP     INP     +      dilate     min     avg  




                                                         cartesian
                                                           genetic
                                                     programming
Wednesday, September 5, 2012
INP               INP     INP     +      dilate     min     avg  




             ()*+,-*"
             .-**/+,-*"%"
             .-**/+,-*"$"
                                         !"
                                        "#$"
                                        "#%"
                                                         cartesian
                                                           genetic
             0"1/23"*)45/1"             &'!"
                                         """
                                           "



                                                     programming
Wednesday, September 5, 2012
detect
Wednesday, September 5, 2012
detect
Wednesday, September 5, 2012
!"#$%&$'()*'+,%-$&+*,.%
                        •      /+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
detecting
        rocks
Wednesday, September 5, 2012
Wednesday, September 5, 2012
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
detecting
             specific
               rocks
Wednesday, September 5, 2012
detectingspecificrocks
Wednesday, September 5, 2012
classifying
             martian
              terrain
Wednesday, September 5, 2012
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
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
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
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
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
conclusions
                 combining cgp with opencv creates possibilities

                 output: executable, human-readable code
                         for detection and identification
                 impressive performance (and robustness)




Wednesday, September 5, 2012
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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Mars Terrain Image Classification Using Cartesian Genetic Programming #isairas 2012

  • 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. thanks to G. Metta and IIT for this picture visual perception Wednesday, September 5, 2012
  • 3. detecting objects Wednesday, September 5, 2012
  • 4. learning approach Wednesday, September 5, 2012
  • 5. INP   INP   INP   +   dilate   min   avg   cartesian genetic programming Wednesday, September 5, 2012
  • 6. Image credit: NASA space applications Wednesday, September 5, 2012
  • 7. Image credit: NASA space applications Wednesday, September 5, 2012
  • 8. cgp approach Wednesday, September 5, 2012
  • 9. INP   INP   INP   +   dilate   min   avg   cartesian genetic programming Wednesday, September 5, 2012
  • 10. INP   INP   INP   +   dilate   min   avg   ()*+,-*" .-**/+,-*"%" .-**/+,-*"$" !" "#$" "#%" cartesian genetic 0"1/23"*)45/1" &'!" """ " programming Wednesday, September 5, 2012
  • 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. detecting rocks Wednesday, September 5, 2012
  • 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. detecting specific rocks Wednesday, September 5, 2012
  • 19. classifying martian terrain Wednesday, September 5, 2012
  • 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. 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. 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. 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. 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. 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. 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