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A Distributed and Multithreaded SLAM Architecture for Robotic Clusters and Wireless Sensor Networks

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Cooperative Robots and Sensor Networks 2015

Part of the book series: Studies in Computational Intelligence ((SCI,volume 604))

Abstract

In this work, we propose an extremely efficient architecture for the Simultaneous Localization and Mapping (SLAM) problem. The architecture makes use of multithreading and workload distribution over a robotic cluster or a wireless sensor network (WSN) in order to parallelize the most widely used Rao-Blackwellized Particle Filter (RBPF) SLAM approach. We apply the method in common computers found in robots and sensor networks, and evaluate the tradeoffs in terms of efficiency, complexity, load balancing and SLAM performance. It is shown that a significant gain in efficiency can be obtained. Furthermore, the method enables us to raise the workload up to values that would not be possible in a single robot solution, thus gaining in localization precision and map accuracy. All the results are extracted from frequently used SLAM datasets available in the Robotics community and a real world testbed is described to show the potential of using the proposed philosophy.

This work was partially carried out in the framework of TIRAMISU project (www.fp7-tiramisu.eu). This project is funded by the European Community’s Seventh Framework Program (FP7/SEC/284747).

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Notes

  1. 1.

    Hadoop is a Java based framework that supports data intensive distributed applications running on large clusters of computers.

  2. 2.

    Callgrind, available in the Valgrind distribution: http://valgrind.org.

  3. 3.

    https://code.google.com/p/protobuf.

  4. 4.

    http://zeromq.org.

  5. 5.

    https://github.com/brNX/gmapping-stateful, Hybrid branch.

  6. 6.

    http://kaspar.informatik.uni-freiburg.de/~slamEvaluation/datasets.php.

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Authors and Affiliations

  1. Institute of Systems and Robotics (ISR), University of Coimbra (UC), Pólo II, 3030-290, Coimbra, Portugal

    David Portugal, Bruno D. Gouveia & Lino Marques

Authors
  1. David Portugal
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  2. Bruno D. Gouveia
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  3. Lino Marques
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Correspondence to Lino Marques .

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Editors and Affiliations

  1. College of Computer and Information Sciences (CCIS), Prince Sultan University, Riyadh, Saudi Arabia, and CISTER/INESC-TEC, ISEP, Polytechnic Institute of Porto, Porto, Portugal

    Anis Koubâa

  2. Depto. Ing. de Sistemas y Automática Escuela Superior de Ingenieros, University of Seville, Sevilla, Spain

    J.Ramiro Martínez-de Dios

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Portugal, D., Gouveia, B.D., Marques, L. (2015). A Distributed and Multithreaded SLAM Architecture for Robotic Clusters and Wireless Sensor Networks. In: Koubâa, A., Martínez-de Dios, J. (eds) Cooperative Robots and Sensor Networks 2015. Studies in Computational Intelligence, vol 604. Springer, Cham. https://doi.org/10.1007/978-3-319-18299-5_6

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  • DOI: https://doi.org/10.1007/978-3-319-18299-5_6

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