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Proactive Human Search for the Designated Person with Prior Context Information in an Undiscovered Environments

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Abstract

This paper describes a scheme for proactive human search for a designated person in an undiscovered indoor environment without human operation or intervention. In designing and developing human identification with prior information a new approach that is robust to illumination and distance variations in the indoor environment is proposed. In addition, a substantial exploration method with an octree structure, suitable for path planning in an office configuration, is employed. All these functionalities are integrated in a message- and component-based architecture for the efficient integration and control of the system. This approach is demonstrated by succeeding human search in the challenging robot mission of the 2009 Robot Grand Challenge Contest.

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References

  1. Robot Grand Challenge Contest, Pohang, Korea: http://eng.piro.re.kr/sub05_02_1.html (2009)

  2. Bellotto, N., Hu, H.: Multimodal perception and recognition of humans with a mobile service robot. In: Proc. of Int. Conf. on Robot. Bio., pp. 401–406 (2008)

  3. Viola, P., Jones, M.: Fast and robust classification using asymmetric adaboost and a detector cascade. Adv. Neural Inf. Process. Syst. 14, 1311–1318 (2002)

    Google Scholar 

  4. Ojala, T., Pietikainen, M., MAaenpAaAa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 971–987 (2002)

    Article  Google Scholar 

  5. Ayala, D., Brunet, P., Juan, P., Navazo, I.: Object representation by means of nonminimal division quadtrees and octrees. ACM Trans. Graph. 4(1), 41–59 (1985)

    Article  Google Scholar 

  6. Navazo, I., Ayala, D., Brunet, P.: A geometric modeler based on the exact octtree representation of polyhedral. Comput. Graph. Forum 5(2), 91–104 (1986)

    Article  Google Scholar 

  7. Choset, H., Burdick, J.: Sensor-based exploration: The hierarchical generalized voronoi graph. Int. J. Rob. Res. 19(2), 96–125 (2000)

    Article  Google Scholar 

  8. Konolige, K.: A gradient method for real-time robot control. In: Proc. of Int. Conf. Intel. Robot. Syst., pp. 639–646 (2000)

  9. Thrun, S., Bennewitz, M., Burgard, W., Cremers, A.B., Dellaert, F., Fox, D., Hahnel, D., Rosenberg, C., Roy, N., Schulte, J., Schulz, D.: MINERVA: a second-generation museum tour-guide robot. In: Proc. of IEEE Int. Conf. Robot. Autom., pp. 10–15 (1999)

  10. Fritsch, J., Kleinehagenbrock, M., Haasch, A., Wrede, S., Sagerer, G.: A flexible infrastructure for the development of a robot companion with extensible HRI-capabilities. In: Proc. of Int. Conf. on Robot. Autom., pp. 3408–3414 (2005)

  11. Weser, M., Jockel, S., Zhang, J.: Fuzzy multisensor fusion for autonomous proactive robot perception. In: Proc. of Int. Conf. on Fuzzy Syst., pp. 2262–2267 (2008)

  12. Gat, E. : On three-layer architectures. In: Kortenkamp D., et al. (eds.) Artificial Intelligence and Mobile Robots, pp. 195–210 (1998, 2004)

  13. Yavuz, H., Bradshaw, A.: A new conceptual approach to the design of hybrid control architecture for autonomous mobile robots. J. Intell. Robot. Syst. 34(1), 1–26 (2002)

    Article  MATH  Google Scholar 

  14. Kim, J., Choi, M.-T., Kim, M., Kim, S., Kim, M., Park, S., Lee, J., Kim, B.: Intelligent robot software architecture. Lect. Notes Control Inf. Sci. 370, 385–397 (2008)

    Article  Google Scholar 

  15. Yun, S., Kim, C.G., Kim, M., Choi, M.-T.: Robust robot’s attention for human based on the multi-modal sensor and robot behavior. In: Proc. of IEEE Workshop on Adv. Robot. Social Impacts, pp. 117–122 (2010)

  16. Makarenko, A.A., Williams, S.B., Bourgault, F., Durrant-Whyte, H.F.: An experiment in integrated exploration. In: Proc. of IEEE Int. Conf. Robot. Syst., pp. 534–539 (2002)

  17. Park, J., Song, J.-B.: Efficient and intelligent exploration for room finding in large-scale environments. In: Proc. of Int. Conf Cont. Autom. Syst., pp. 3188–3192 (2009)

  18. Seo, J., Kim, J, Lee, S., Park, Y.: A novel octree partitioning approach based on camera parameters for unknown object representation. In: Proc. of Int. Conf. Mech. Info. Tech. (2007). doi:10.1117/12.784520

  19. Kim, J., Lee, S.: Fast neighbor cells finding method for multiple octree representation. In: Proc. of IEEE Int. Symp. Comp. Intel. Robot. Autom., pp. 540–545 (2009)

  20. Jin, H., Liu, Q., Lu, H., Tong, X.: Face detection using improved LBP under bayesian framework. In: Proc. of Int. Conf. on Image and Graphics, pp. 306–309 (2007)

  21. Ahonen, T., Hadid, A., Pietikainen, M.: Face description with local binary patterns: application to face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 28(12), 2037–2041 (2006)

    Article  Google Scholar 

  22. Lee, H.-S., Park, S., Kang, B., Shin, J., Lee, J.Y., Je, H., M., Jun, B., Kim, D.: The POSTECH face database (PF07) and performance evaluation. In: Proc. of IEEE Int. Conf. on Automatic Face and Gesture Recognition, pp. 1–6 (2008)

  23. Wang, H., Li, S., Wang, Y., Zhang, J.: Self quotient image for face recognition. In: Proc. of Int. Conf. on Image Processing, pp. 1397–1400 (2004)

  24. Tan, X., Triggs, B.: Enhanced local texture feature sets for face recognition under difficult lighting conditions. In: Proc. of Analysis and Modeling of Faces and Gestures, pp. 168–182 (2007)

  25. Face Detection Database, POSTECH, Korea: http://imlab.postech.ac.kr/faceDB/FDD06/FDD06.html (2006)

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Authors and Affiliations

  1. Department of Mechanical Engineering, Korea University, Seoul, Korea

    Sangseok Yun, Joong-Tae Park & Jae-Bok Song

  2. Center for Intelligent Robotics at Korea Institute and Technology (KIST), Seoul, Korea

    Sangseok Yun, Mun-Taek Choi & Munsang Kim

  3. Department of Computer Science and Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Korea

    Bongjin Jun & Daijin Kim

  4. School of Information and Communication Engr., Sungkyunkwan University, Suwon, Korea

    Jaewoong Kim & Sukhan Lee

Authors
  1. Sangseok Yun
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  2. Bongjin Jun
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  3. Daijin Kim
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  4. Jaewoong Kim
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  5. Sukhan Lee
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  6. Mun-Taek Choi
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  7. Munsang Kim
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  8. Joong-Tae Park
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  9. Jae-Bok Song
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Correspondence to Mun-Taek Choi.

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Yun, S., Jun, B., Kim, D. et al. Proactive Human Search for the Designated Person with Prior Context Information in an Undiscovered Environments. J Intell Robot Syst 67, 79–99 (2012). https://doi.org/10.1007/s10846-011-9641-x

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  • DOI: https://doi.org/10.1007/s10846-011-9641-x

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