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    Peer-to-Peer Relative Localization of Aerial Robots With Ultrawideband Sensors

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    TransCST_200327_2.pdf
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    3.480Mb
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    Description:
    Accepted manuscript
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    Type
    Article
    Authors
    Güler, Samet cc
    Abdelkader, Mohamed
    Shamma, Jeff S. cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    RISC Laboratory
    Date
    2020-10-08
    Online Publication Date
    2020-10-08
    Print Publication Date
    2021-09
    Submitted Date
    2019-04-22
    Permanent link to this record
    http://hdl.handle.net/10754/665552
    
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    Abstract
    Robots in swarms take advantage of localization infrastructure, such as a motion capture system or global positioning system (GPS) sensors to obtain their global position, which can then be communicated to other robots for swarm coordination. However, the availability of localization infrastructure needs not to be guaranteed, e.g., in GPS-denied environments. Likewise, the communication overhead associated with broadcasting locations may be undesirable. For reliable and versatile operation in a swarm, robots must sense each other and interact locally. Motivated by this requirement, we propose an onboard relative localization framework for multirobot systems. The setup consists of an anchor robot with three onboard ultrawideband (UWB) sensors and a tag robot with a single onboard UWB sensor. The anchor robot utilizes the three UWB sensors to estimate the tag robot's location by using its onboard sensing and computational capabilities solely, without explicit interrobot communication. Because the anchor UWB sensors lack the physical separation that is typical in fixed UWB localization systems, we introduce filtering methods to improve the estimation of the tag's location. In particular, we utilize a mixture Monte Carlo localization (MCL) approach to capture maneuvers of the tag robot with acceptable precision. We validate the effectiveness of our algorithm with simulations as well as indoor and outdoor field experiments on a two-drone setup. The proposed mixture MCL algorithm yields highly accurate estimates for various speed profiles of the tag robot and demonstrates superior performance over the standard particle filter and the extended Kalman filter.
    Citation
    Guler, S., Abdelkader, M., & Shamma, J. S. (2020). Peer-to-Peer Relative Localization of Aerial Robots With Ultrawideband Sensors. IEEE Transactions on Control Systems Technology, 1–16. doi:10.1109/tcst.2020.3027627
    Sponsors
    The authors would like to thank Kuat Telegenov for his support in experiments.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    IEEE Transactions on Control Systems Technology
    DOI
    10.1109/TCST.2020.3027627
    Additional Links
    https://ieeexplore.ieee.org/document/9217573/
    https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9217573
    ae974a485f413a2113503eed53cd6c53
    10.1109/TCST.2020.3027627
    Scopus Count
    Collections
    Articles; Electrical and Computer Engineering Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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