Attention-Based Landmark Selection in Autonomous Robotics

  • Antonio Chella
  • Irene Macaluso
  • Lorenzo Riano
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4840)


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.


Mobile Robot Visual Attention Robot Navigation Robot Position Landmark Position 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Antonio Chella
    • 1
  • Irene Macaluso
    • 1
  • Lorenzo Riano
    • 1
  1. 1.Università degli studi di Palermo, Dipartimento di Ingegneria Informatica, Viale delle Scienze ed. 6Italy

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