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Mobile Robot Planning Using Action Language \({\mathcal {BC}}\) with an Abstraction Hierarchy

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Logic Programming and Nonmonotonic Reasoning (LPNMR 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9345))

Abstract

Planning in real-world environments can be challenging for intelligent robots due to incomplete domain knowledge that results from unpredictable domain dynamism, and due to lack of global observability. Action language \(\mathcal{BC}\) can be used for planning by formalizing the preconditions and (direct and indirect) effects of actions, and is especially suited for planning in robotic domains by incorporating defaults with the incomplete domain knowledge. However, planning with \(\mathcal{BC}\) is very computationally expensive, especially when action costs are considered. We introduce algorithm PlanHG for formalizing \(\mathcal{BC}\) domains at different abstraction levels in order to trade optimality for significant efficiency improvement when aiming to minimize overall plan cost. We observe orders of magnitude improvement in efficiency compared to a standard “flat” planning approach.

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Notes

  1. 1.

    As a preprocessing step, computing \(\mathcal{L}\) does not affect the runtime efficiency, so we leave the discussion of its complexity to future work.

  2. 2.

    https://youtu.be/-QpFj7BbiRU.

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Acknowledgments

This work has taken place in the Learning Agents Research Group (LARG) at the Artificial Intelligence Laboratory, The University of Texas at Austin. LARG research is supported in part by grants from the National Science Foundation (CNS-1330072, CNS-1305287), ONR (21C184-01), AFOSR (FA8750-14-1-0070, FA9550-14-1-0087), and Yujin Robot.

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Authors and Affiliations

  1. Department of Computer Science, The University of Texas at Austin, 2317 Speedway, Stop D9500, Austin, TX, 78712, USA

    Shiqi Zhang, Piyush Khandelwal & Peter Stone

  2. Schlumberger Software Technology, Schlumberger Ltd, 5599 San Felipe Rd, Houston, TX, 77056, USA

    Fangkai Yang

Authors
  1. Shiqi Zhang
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  2. Fangkai Yang
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  3. Piyush Khandelwal
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  4. Peter Stone
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Corresponding author

Correspondence to Shiqi Zhang .

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Editors and Affiliations

  1. University of Calabria, Rende, Italy

    Francesco Calimeri

  2. University of Calabria, Rende, Italy

    Giovambattista Ianni

  3. University of Kentucky Dept. Computer Science, Lexington, Kentucky, USA

    Miroslaw Truszczynski

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Zhang, S., Yang, F., Khandelwal, P., Stone, P. (2015). Mobile Robot Planning Using Action Language \({\mathcal {BC}}\) with an Abstraction Hierarchy. In: Calimeri, F., Ianni, G., Truszczynski, M. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2015. Lecture Notes in Computer Science(), vol 9345. Springer, Cham. https://doi.org/10.1007/978-3-319-23264-5_42

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  • DOI: https://doi.org/10.1007/978-3-319-23264-5_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23263-8

  • Online ISBN: 978-3-319-23264-5

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