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Multi-Robot Localization and Mapping Based on Signed Distance Functions

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Abstract

This publication describes a 2D Simultaneous Localization and Mapping approach applicable to multiple mobile robots. The presented strategy uses data of 2D LIDAR sensors to build a dynamic representation based on Signed Distance Functions. Novelties of the approach are a joint map built in parallel instead of occasional merging of smaller maps and the limited drift localization which requires no loop closure detection. A multi-threaded software architecture performs registration and data integration in parallel allowing for drift-reduced pose estimation of multiple robots. Experiments are provided demonstrating the application with single and multiple robot mapping using simulated data, public accessible recorded data, two actual robots operating in a comparably large area as well as a deployment of these units at the Robocup rescue league.

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Authors and Affiliations

  1. Faculty of Electrical Engineering, Precision Engineering, Information Technology, Nuremberg Institute of Technology Georg Simon Ohm, Nuremberg, Germany

    Philipp Koch, Stefan May, Michael Schmidpeter, Markus Kühn, Christian Pfitzner, Christian Merkl, Rainer Koch, Martin Fees, Jon Martin & Daniel Ammon

  2. Informatics VII: Robotics and Telematics, University Wuerzburg, Würzburg, Germany

    Daniel Ammon & Andreas Nüchter

Authors
  1. Philipp Koch
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  2. Stefan May
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  3. Michael Schmidpeter
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  4. Markus Kühn
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  5. Christian Pfitzner
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  6. Christian Merkl
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  7. Rainer Koch
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  8. Martin Fees
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  9. Jon Martin
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  10. Daniel Ammon
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  11. Andreas Nüchter
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Correspondence to Philipp Koch.

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Koch, P., May, S., Schmidpeter, M. et al. Multi-Robot Localization and Mapping Based on Signed Distance Functions. J Intell Robot Syst 83, 409–428 (2016). https://doi.org/10.1007/s10846-016-0375-7

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  • DOI: https://doi.org/10.1007/s10846-016-0375-7

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