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    Cooperative multi-target localization with noisy sensors

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    Genre
    Conference Proceeding
    Date
    2013-11-14
    Author
    Dames, P
    Kumar, V
    Subject
    cs.RO
    cs.RO
    cs.MA
    Permanent link to this record
    http://hdl.handle.net/20.500.12613/5929
    
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    DOI
    10.1109/ICRA.2013.6630825
    Abstract
    This paper addresses the task of searching for an unknown number of static targets within a known obstacle map using a team of mobile robots equipped with noisy, limited field-of-view sensors. Such sensors may fail to detect a subset of the visible targets or return false positive detections. These measurement sets are used to localize the targets using the Probability Hypothesis Density, or PHD, filter. Robots communicate with each other on a local peer-to-peer basis and with a server or the cloud via access points, exchanging measurements and poses to update their belief about the targets and plan future actions. The server provides a mechanism to collect and synthesize information from all robots and to share the global, albeit time-delayed, belief state to robots near access points. We design a decentralized control scheme that exploits this communication architecture and the PHD representation of the belief state. Specifically, robots move to maximize mutual information between the target set and measurements, both self-collected and those available by accessing the server, balancing local exploration with sharing knowledge across the team. Furthermore, robots coordinate their actions with other robots exploring the same local region of the environment. © 2013 IEEE.
    Citation to related work
    IEEE
    Has part
    Proceedings - IEEE International Conference on Robotics and Automation
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    For Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.edu
    ae974a485f413a2113503eed53cd6c53
    http://dx.doi.org/10.34944/dspace/5911
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