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Probabilistic Boundary Coverage for Unknown Target Fields with Large Perception Uncertainty and Limited Sensing Range

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Part of the book series: Springer Proceedings in Advanced Robotics ((SPAR,volume 10))

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Abstract

We introduce a new type of probabilistic boundary coverage problem where a robot has to enclose unknown target fields (UTFs) with large perception uncertainty and limited sensing range. When the robot gets closer to UTF and accumulates sufficient sensory readings, it employs Gaussian processes (GPs) as a local belief function to approximate field boundary distribution in an ellipse-shaped local region. The local belief function allows us to predict UTF boundary trends and establish an adjacent ellipse for further exploration. The process is governed by a depth-first search process until UTF is approximately enclosed by connected ellipses when the boundary coverage process ends. We formally prove that our boundary coverage process guarantees the enclosure above a given coverage ratio with a preset probability threshold. We have implemented our algorithm and tested it under different field types in simulation.

This work was supported in part by National Science Foundation under IIS-1318638, NRI-1426752, NRI-1526200, and NRI-1748161.

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Acknowledgements

Thanks for C. Chou, H. Cheng, S. Yeh, A. Kingery, A. Angert, H. Li, and T. Sun for their inputs and Y. Sun, M. Jin, D. Wang, and Y. Yu for their contributions to the NetBot Laboratory, Texas A&M University.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Texas A&M University, College Station, TX, 77843, USA

    Binbin Li & Dezhen Song

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  1. Binbin Li
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  2. Dezhen Song
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Correspondence to Dezhen Song .

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Editors and Affiliations

  1. Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Nancy M. Amato

  2. Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA

    Greg Hager

  3. Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA

    Shawna Thomas

  4. Department of Electrical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile

    Miguel Torres-Torriti

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Li, B., Song, D. (2020). Probabilistic Boundary Coverage for Unknown Target Fields with Large Perception Uncertainty and Limited Sensing Range. In: Amato, N., Hager, G., Thomas, S., Torres-Torriti, M. (eds) Robotics Research. Springer Proceedings in Advanced Robotics, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-030-28619-4_50

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