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Spatial Understanding as a Common Basis for Human-Robot Collaboration

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Advances in Human Factors in Robots and Unmanned Systems (AHFE 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 595))

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We are developing a robotic cognitive architecture to be embedded in autonomous robots that can safely interact and collaborate with people on a wide range of physical tasks. Achieving true autonomy requires increasing the robot’s understanding of the dynamics of its world (physical understanding), and particularly the actions of people (cognitive understanding). Our system’s cognitive understanding arises from the Soar cognitive architecture, which constitutes the reasoning and planning component. The system’s physical understanding stems from its central representation, which is a 3D virtual world that the architecture synchronizes with the environment in real time. The virtual world provides a common representation between the robot and humans, thus improving trust between them and promoting effective collaboration.

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  1. Oliva, A., Torralba, A.: The role of context in object recognition. Trends Cogn. Sci. 11(12), 520–527 (2008)

    Article  Google Scholar 

  2. Marr, D.: Vision. W. H. Freeman, San Francisco (1982)

    Google Scholar 

  3. Hanson, A., Riseman, E.: Visions: a computer system for interpreting scenes. In: Hanson, A., Riseman, E. (eds.) Computer Vision. Academic Press, New York (1978)

    Google Scholar 

  4. Csurka, G., et al.: Visual categorization with bags of keypoints. In: Workshop on Statistical Learning in Computer Vision, ECCV, vol. 1 (2004)

    Google Scholar 

  5. Mortensen, E., Deng, H., Shapiro, L.: A SIFT descriptor with global context. In: International Conference on Computer Vision and Pattern Recognition (2005)

    Google Scholar 

  6. Marques, O., Barenholtz, E., Charvillat, V.: Context modelling in computer vision: techniques, implications and applications. Multimed. Tools Appl. 51, 303–339 (2011)

    Article  Google Scholar 

  7. Ungar, S.: Cognitive mapping without visual experience. In: Kitchin, R., Freundschuh, S. (eds.) Cognitive Mapping: Past Present and Future. Routledge, London (2000)

    Google Scholar 

  8. Shanahan, M.P.: A cognitive architecture that combines internal simulation with a global workspace. Conscious. Cogn. 15, 433–449 (2006)

    Article  Google Scholar 

  9. Pezzulo, G., et al.: The mechanics of embodiment: a dialog on embodiment and computational modeling. Front. Psychol. 2, A5 (2011)

    Google Scholar 

  10. Rayner, K.: Eye movements and cognitive processes in reading, visual search, and scene perception. In: Findlay, J.M., Walker, R., Kentridge, R.W. (eds.) Eye Movement Research: Mechanisms, Processes, and Applications, pp. 3–21. Elsevier, New York (1995)

    Chapter  Google Scholar 

  11. Barnes, N., Liu, Z.-Q.: Embodied computer vision for mobile robots. In: ICIPS 1997, pp. 1395–1399 (1997). doi:10.1109/ICIPS.1997.669238

  12. Benjamin, D.P., Lyons, D., Monaco, J.V., Lin, Y., Funk, C.: Using a virtual world for robot planning. In: SPIE Conference on Multisensor, Multisource Information Fusion (2012).

  13. Lyons, D., Nirmal, P., Benjamin, D.P.: Navigation of uncertain terrain by fusion of information from real and synthetic imagery. In: SPIE Conference on Multisensor, Multisource Information Fusion (2012).

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Correspondence to D. Paul Benjamin .

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Benjamin, D.P., Li, T., Shen, P., Yue, H., Zhao, Z., Lyons, D. (2018). Spatial Understanding as a Common Basis for Human-Robot Collaboration. In: Chen, J. (eds) Advances in Human Factors in Robots and Unmanned Systems. AHFE 2017. Advances in Intelligent Systems and Computing, vol 595. Springer, Cham.

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  • Print ISBN: 978-3-319-60383-4

  • Online ISBN: 978-3-319-60384-1

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