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Multi-vehicle Dynamic Pursuit Using Underwater Acoustics

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Robotics Research

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 114))

Abstract

Marine robots communicating wirelessly is an increasingly attractive means for observing and monitoring the ocean, but acoustic communication remains a major impediment to real-time control. In this paper we address through experiments the capability of acoustics to sustain highly dynamic, multi-agent missions, in particular range-only pursuit in a challenging shallow-water environment. We present in detail results comparing the tracking performance of three different communication configurations, at operating speeds near 1.5 m/s. A “lower bound” case with RF wireless communication, a 4-second cycle and no quantization has a tracking bandwidth of \(\approx \)0.5 rad/s. When using full-sized modem packets with negligible quantization and a 23-second cycle time, the tracking bandwidth is \(\approx \)0.065 rad/s. With 13-bit mini-packets, we employ logarithmic quantization to achieve a cycle time of 12 s and a tracking bandwidth of \(\approx \)0.13 rad/s. These outcomes show definitively that aggressive dynamic control of multi-agent systems underwater is tractable today.

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Notes

  1. 1.

    The linear form written is based on approximation of the tangent function. For errors less than 1 m, the MOOS Trackline controller increases the lead distance proportionally, effectively lowering the gain to limit oscillations.

  2. 2.

    When range measurements do not interfere with modem packets and the cycle consists of just two-way communications (e.g. using GPS and wifi for ranges), we have achieved a 6-second total cycle time with mini-packets in the field.

  3. 3.

    As we were submitting this paper we became aware of several modifications in the operation of the Micro-Modems that likely will allow for slightly faster cycle times.

  4. 4.

    Other nonlinear, range-only filters, such as particle filters, could also be used [15].

  5. 5.

    The ranges are set relative to the distance the target can drive in a time step, so that the target is unlikely to cross the baseline before the control system can react.

  6. 6.

    This data set, along with videos, is publicly available at http://web.mit.edu/hovergroup/resources.html.

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Acknowledgments

Work is supported by the Office of Naval Research, Grant N00014-09-1-0700, the National Science Foundation, Contract CNS-1212597, and the Finmeccanica Career Development Professorship. We thank Mei Cheung for providing Fig. 4 and help with experimental implementation. We thank Toby Schneider and Mike Benjamin at MIT, and Keenan Ball and Sandipa Singh at WHOI, for their help on technical items. We also acknowledge MIT Sailing Master Fran Charles.

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Authors and Affiliations

  1. MIT/WHOI Joint Program in Oceanographic Engineering, Cambridge, USA

    Brooks Reed

  2. Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA

    Josh Leighton & Franz Hover

  3. Northeastern University, 360 Huntington Ave., Boston, MA, 02115, USA

    Milica Stojanovic

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  1. Brooks Reed
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  2. Josh Leighton
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  3. Milica Stojanovic
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  4. Franz Hover
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Corresponding author

Correspondence to Brooks Reed .

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Editors and Affiliations

  1. Creative Informatics, The University of Tokyo, Tokyo, Japan

    Masayuki Inaba

  2. School of Electrical Engineering and Com, Queensland Univ of Technology, Brisbane, Queensland, Australia

    Peter Corke

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Reed, B., Leighton, J., Stojanovic, M., Hover, F. (2016). Multi-vehicle Dynamic Pursuit Using Underwater Acoustics. In: Inaba, M., Corke, P. (eds) Robotics Research. Springer Tracts in Advanced Robotics, vol 114. Springer, Cham. https://doi.org/10.1007/978-3-319-28872-7_5

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  • DOI: https://doi.org/10.1007/978-3-319-28872-7_5

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  • Online ISBN: 978-3-319-28872-7

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