The Robot-at-Home dataset (Robot@Home, paper here) is a collection of raw and processed data from five domestic settings compiled by a mobile robot equipped with 4 RGB-D cameras and a 2D laser scanner. Its main purpose is to serve as a testbed for semantic mapping algorithms through the categorization of objects and/or rooms. This dataset is unique in three aspects: The provided data were captured with a rig of 4 RGB-D sensors with an overall field of view of 180°H. and 58°V., and with a 2D laser scanner. It comprises diverse and numerous data: sequences of RGB-D images and laser scans from the rooms of five apartments (87,000+ observations were collected), topological information about the connectivity of these rooms, and 3D reconstructions and 2D geometric maps of the visited rooms. The provided ground truth is dense, including per-point annotations of the categories of the objects and rooms appearing in the reconstructed scenarios, and per-pixel annotations of each RGB-D image within the recorded sequences During the data collection, a total of 36 rooms were completely inspected, so the dataset is rich in contextual information of objects and rooms. This is a valuable feature, missing in most of the state-of-the-art datasets, which can be exploited by, for instance, semantic mapping systems that leverage relationships like pillows are usually on beds or ovens are not in bathrooms. ; This work was supported by the Spanish projects "IRO: Improvement of the sensorial and autonomous capability of robots through olfaction" (2012-TEP-530), "PROMOVE: Advances in mobile robotics for promoting independent life of elders" (DPI2014-55826-R), and "WISER: Building and exploiting semantic maps by mobile robots" (DPI2017-84827-R), the European project "MoveCare: Multiple-actors virtual empathic caregiver for the elder" (Call: H2020-ICT-2016-1, contract number: 732158) and by a postdoc contract from the I-PPIT from the University of Malaga.


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    Titel :

    Robot@Home, a robotic dataset for semantic mapping of home environments



    Erscheinungsdatum :

    2017-03-13


    Anmerkungen:

    The International Journal of Robotics Research 36(2) 131-141



    Medientyp :

    Forschungsdaten


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629




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