Decentralized Active Information Acquisition: Theory and Application to Multi-Robot SLAM
Nikolay A. Atanasov, Jerome Le Ny, Kostas Daniilidis, George Pappas

Citation
Nikolay A. Atanasov, Jerome Le Ny, Kostas Daniilidis, George Pappas. "Decentralized Active Information Acquisition: Theory and Application to Multi-Robot SLAM". IEEE International Conference on Robotics and Automation (ICRA), 26, May, 2015; Submitted.

Abstract
This paper addresses the problem of controlling mobile sensing systems in order to improve the accuracy and efficiency of information acquisition. It applies to scenarios such as environmental monitoring, search and rescue, surveillance and reconnaissance, and simultaneous localization and mapping (SLAM). A multi-sensor active information acquisition problem capturing the common characteristics of these scenarios is formulated. The goal is to design control policies for the sensors, which minimize the entropy of the estimation task conditioned on the future measurements. First, we provide a non-greedy centralized solution, which is computationally fast, as it exploits linearized sensing models, and memory efficient, as it exploits sparsity in the environment model. Next, we decentralize the control to obtain linear complexity in the number of sensors and provide suboptimality guarantees. When applied to the multi-robot active SLAM problem, our results enable a decentralized nonmyopic solution that exploits sparsity in the planning process.

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  • HTML
    Nikolay A. Atanasov, Jerome Le Ny, Kostas Daniilidis, George
    Pappas. <a
    href="http://www.terraswarm.org/pubs/383.html"
    >Decentralized Active Information Acquisition: Theory and
    Application to Multi-Robot SLAM</a>, IEEE
    International Conference on Robotics and Automation (ICRA),
    26, May, 2015; Submitted.
  • Plain text
    Nikolay A. Atanasov, Jerome Le Ny, Kostas Daniilidis, George
    Pappas. "Decentralized Active Information Acquisition:
    Theory and Application to Multi-Robot SLAM". IEEE
    International Conference on Robotics and Automation (ICRA),
    26, May, 2015; Submitted.
  • BibTeX
    @inproceedings{AtanasovLeNyDaniilidisPappas15_DecentralizedActiveInformationAcquisitionTheoryApplication,
        author = {Nikolay A. Atanasov and Jerome Le Ny and Kostas
                  Daniilidis and George Pappas},
        title = {Decentralized Active Information Acquisition:
                  Theory and Application to Multi-Robot SLAM},
        booktitle = {IEEE International Conference on Robotics and
                  Automation (ICRA)},
        day = {26},
        month = {May},
        year = {2015},
        note = {Submitted},
        abstract = {This paper addresses the problem of controlling
                  mobile sensing systems in order to improve the
                  accuracy and efficiency of information
                  acquisition. It applies to scenarios such as
                  environmental monitoring, search and rescue,
                  surveillance and reconnaissance, and simultaneous
                  localization and mapping (SLAM). A multi-sensor
                  active information acquisition problem capturing
                  the common characteristics of these scenarios is
                  formulated. The goal is to design control policies
                  for the sensors, which minimize the entropy of the
                  estimation task conditioned on the future
                  measurements. First, we provide a non-greedy
                  centralized solution, which is computationally
                  fast, as it exploits linearized sensing models,
                  and memory efficient, as it exploits sparsity in
                  the environment model. Next, we decentralize the
                  control to obtain linear complexity in the number
                  of sensors and provide suboptimality guarantees.
                  When applied to the multi-robot active SLAM
                  problem, our results enable a decentralized
                  nonmyopic solution that exploits sparsity in the
                  planning process.},
        URL = {http://terraswarm.org/pubs/383.html}
    }
    

Posted by Nikolay A. Atanasov on 1 Oct 2014.
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