Show Reference: "Persistent Navigation and Mapping using a Biologically Inspired SLAM System"

Persistent Navigation and Mapping using a Biologically Inspired SLAM System The International Journal of Robotics Research, Vol. 29, No. 9. (1 August 2010), pp. 1131-1153, doi:10.1177/0278364909340592 by Michael Milford, Gordon Wyeth
@article{milford-and-wyeth-2010,
    abstract = {The challenge of persistent navigation and mapping is to develop an autonomous                     robot system that can simultaneously localize, map and navigate over the                     lifetime of the robot with little or no human intervention. Most solutions to                     the simultaneous localization and mapping ({SLAM}) problem aim to produce highly                     accurate maps of areas that are assumed to be static. In contrast, solutions for                     persistent navigation and mapping must produce reliable goal-directed navigation                     outcomes in an environment that is assumed to be in constant flux. We                     investigate the persistent navigation and mapping problem in the context of an                     autonomous robot that performs mock deliveries in a working office environment                     over a two-week period. The solution was based on the biologically inspired                     visual {SLAM} system, {RatSLAM}. {RatSLAM} performed {SLAM} continuously while                     interacting with global and local navigation systems, and a task selection                     module that selected between exploration, delivery, and recharging modes. The                     robot performed 1,143 delivery tasks to 11 different locations with only one                     delivery failure (from which it recovered), traveled a total distance of more                     than 40 km over 37 hours of active operation, and recharged autonomously a total                     of 23 times.},
    author = {Milford, Michael and Wyeth, Gordon},
    day = {1},
    doi = {10.1177/0278364909340592},
    journal = {The International Journal of Robotics Research},
    keywords = {ann, architecture, grid\_cells, model, ratslam, slam, unsupervised-learning, visual, vslam},
    month = aug,
    number = {9},
    pages = {1131--1153},
    posted-at = {2012-04-18 16:59:29},
    priority = {0},
    title = {Persistent Navigation and Mapping using a Biologically Inspired {SLAM} System},
    url = {http://dx.doi.org/10.1177/0278364909340592},
    volume = {29},
    year = {2010}
}

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