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Attention-Based Landmark Selection in Autonomous Robotics

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Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint (WAPCV 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4840))

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Abstract

This paper describes a robotic architecture that uses visual attention mechanisms for autonomous navigation in unknown indoor environments. A foveation mechanism based on a bottom-up attention system allows the robot to autonomously select landmarks, defined as salient points in the camera images. Landmarks are memorized in a behavioral fashion by coupling sensing and acting to achieve a representation that is view and scale independent. Selected landmarks are stored in a topological map. During the navigation a top-down mechanism controls the attention system to achieve robot localization. Experiments and results show that our system is robust to noise and odometric errors, being at the same time able to deal with a wide range of different environments.

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Authors and Affiliations

  1. Università degli studi di Palermo, Dipartimento di Ingegneria Informatica, Viale delle Scienze ed. 6, Italy

    Antonio Chella, Irene Macaluso & Lorenzo Riano

Authors
  1. Antonio Chella
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  2. Irene Macaluso
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  3. Lorenzo Riano
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Editor information

Editors and Affiliations

  1. Joanneum Research, Forschungsgesellschaft mbH, Computational Perception Group,, Institute of Digital Image Processing, Wastiangasse 6, 8010, Graz, Austria

    Lucas Paletta

  2. Autonomous Intelligent Systems (AIS), Autonomous Robots Department, Fraunhofer Institute, Schloss Birlinghoven, 53754, Sankt Augustin, Germany

    Erich Rome

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© 2007 Springer-Verlag Berlin Heidelberg

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Chella, A., Macaluso, I., Riano, L. (2007). Attention-Based Landmark Selection in Autonomous Robotics. In: Paletta, L., Rome, E. (eds) Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint. WAPCV 2007. Lecture Notes in Computer Science(), vol 4840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77343-6_29

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  • DOI: https://doi.org/10.1007/978-3-540-77343-6_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77342-9

  • Online ISBN: 978-3-540-77343-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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