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Toward Robot Perception through Omnidirectional Vision

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Innovations in Intelligent Machines - 1

Part of the book series: Studies in Computational Intelligence ((SCI,volume 70))

Vision is an extraordinarily powerful sense. The ability to perceive the environment allows for movement to be regulated by the world. Humans do this effortlessly but we still lack an understanding of how perception works. Our approach to gaining an insight into this complex problem is to build artificial visual systems for semi-autonomous robot navigation, supported by humanrobot interfaces for destination specification. We examine how robots can use images, which convey only 2D information, in a robust manner to drive its actions in 3D space. Our work provides robots with the perceptual capabilities to undertake everyday navigation tasks, such as go to the fourth office in the second corridor. We present a complete navigation system with a focus on building – in line with Marr’s theory [57] – mediated perception modalities. We address fundamental design issues associated with this goal; namely sensor design, environmental representations, navigation control and user interaction.

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Authors and Affiliations

  1. Instituto de Sistemas e Robótica, Instituto Superior Técnico, Av. Rovisco Pais, 1, 1049-001, Lisboa, Portugal

    José Gaspar, Etienne Grossmann & José Santos- Victor

  2. London Knowledge Lab, 23-29 Emerald St, 3QS, London, WC1N, UK

    Niall Winters

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  1. José Gaspar
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  4. José Santos- Victor
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Editors and Affiliations

  1. Defence Science and Technology Organisation, Edinburgh, South Australia, Australia

    Javaan Singh Chahl

  2. University of South Australia Mawson Lakes Campus, Adelaide, South Australia, Australia

    Lakhmi C. Jain

  3. Odonatrix Pty Ltd., Adelaide, South Australia, Australia

    Akiko Mizutani

  4. University of Tsukuba, Japan

    Mika Sato-Ilic

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Gaspar, J., Winters, N., Grossmann, E., Victor, J.S. (2007). Toward Robot Perception through Omnidirectional Vision. In: Chahl, J.S., Jain, L.C., Mizutani, A., Sato-Ilic, M. (eds) Innovations in Intelligent Machines - 1. Studies in Computational Intelligence, vol 70. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72696-8_9

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