This paper addresses visual object perception applied to mobile robotics. Being able to perceive household objects in unstructured environments is a key capability in order to make robots suitable to perform complex tasks in home environments. However, finding a solution for this task is daunting: it requires the ability to handle the variability in image formation in a moving camera with tight time constraints. The paper brings to attention some of the issues with applying three state of the art object recognition and detection methods in a mobile robotics scenario, and proposes methods to deal with windowing/segmentation. Thus, this work aims at evaluating the state-of-the-art in object perception in an attempt to develop a lightweight solution for mobile robotics use/research in typical indoor settings. © Springer Science+Business Media B.V. 2012. ; This work was supported by the following grants: JAE Doc of the CSIC, FEDER European Social funds, AGAUR grant 2009-SGR-1434, the Government of Spain under research programme Consolider Ingenio 2 010: MIPRCV (CSD2007-00018) and MICINN project TIN2011-25606 (SiMeVé), Rio Tinto Centre for Mine Automation, and the ARC Centre of Excellence programme, funded by the Australian Research Council and the New South Wales State Government. ; Peer Reviewed


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    Title :

    Evaluation of three vision based object perception methods for a mobile robot



    Publication date :

    2012-01-01



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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