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Byzantine Fault Tolerant Consensus for Lifelong and Online Multi-robot Pickup and Delivery

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Book cover Distributed Autonomous Robotic Systems (DARS 2021)

Part of the book series: Springer Proceedings in Advanced Robotics ((SPAR,volume 22))

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Abstract

Lifelong and online Multi-Agent Pickup and Delivery is a task and path planning problem in which tasks arrive over time. Real-world applications may require decentralized solutions that do not currently exist. This work proposes a decentralized and Byzantine fault tolerant algorithm building upon blockchain that is competitive against current distributed task and path planning algorithms. At every timestep agents can query the blockchain to receive their best available task pairing and propose a transaction that contains their planned path. This transaction is voted upon by the blockchain network nodes and is stored in the replicated state across all nodes or is rejected, forcing the agent to re-plan. We demonstrate our approach in simulation, showing that it gains the decentralized Byzantine fault tolerant consensus for planning, while remaining competitive against current solutions in its makespan and service time.

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Acknowledgement

This work was partially funded by ARL DCIST CRA W911NF-17-2-0181.

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Authors and Affiliations

  1. University of Southern California, Los Angeles, CA, 90007, USA

    Kegan Strawn & Nora Ayanian

Authors
  1. Kegan Strawn
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  2. Nora Ayanian
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Corresponding author

Correspondence to Kegan Strawn .

Editor information

Editors and Affiliations

  1. Mechanical Engineering and Science, Kyoto University, Kyoto, Japan

    Fumitoshi Matsuno

  2. Mechanical Systems Engineering, Nagoya University, Nagoya, Japan

    Shun-ichi Azuma

  3. Computer Science and Information Technology, Hokkaido University, Sapporo, Hokkaido, Japan

    Masahito Yamamoto

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Strawn, K., Ayanian, N. (2022). Byzantine Fault Tolerant Consensus for Lifelong and Online Multi-robot Pickup and Delivery. In: Matsuno, F., Azuma, Si., Yamamoto, M. (eds) Distributed Autonomous Robotic Systems. DARS 2021. Springer Proceedings in Advanced Robotics, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-030-92790-5_3

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