Automatic Landmark Detection and Recognition in Autonomous Robotics

A Chella, I Macaluso, Lorenzo Riano

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    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.
    Original languageEnglish
    Title of host publicationUnknown Host Publication
    PublisherInternational Joint Conferences on Artificial Intelligence Organization
    Number of pages8
    Publication statusPublished - 2007
    EventProc. of IJCAI 2007, International Workshop on Attention in Cognitive Systems -
    Duration: 1 Jan 2007 → …

    Conference

    ConferenceProc. of IJCAI 2007, International Workshop on Attention in Cognitive Systems
    Period1/01/07 → …

    Fingerprint Dive into the research topics of 'Automatic Landmark Detection and Recognition in Autonomous Robotics'. Together they form a unique fingerprint.

  • Cite this

    Chella, A., Macaluso, I., & Riano, L. (2007). Automatic Landmark Detection and Recognition in Autonomous Robotics. In Unknown Host Publication International Joint Conferences on Artificial Intelligence Organization. http://isrc.ulster.ac.uk/images/stories/Staff/Robotics/Members/LRiano/Documents/ijcai2007.pdf