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Cooperative Route Planning Framework for Multiple Distributed Assets in Maritime Applications

Published: 11 June 2022 Publication History

Abstract

This work formalizes the Route Planning Problem (RPP), wherein a set of distributed assets (e.g., ships, submarines, unmanned systems) simultaneously plan routes to optimize a team goal (e.g., find the location of an unknown threat or object in minimum time and/or fuel consumption) while ensuring that the planned routes satisfy certain constraints (e.g., avoiding collisions and obstacles). This problem becomes overwhelmingly complex for multiple distributed assets as the search space grows exponentially to design such plans. The RPP is formalized as a Team Discrete Markov Decision Process (TDMDP) and we propose a Multi-agent Multi-objective Reinforcement Learning (MaMoRL) framework for solving it. We investigate challenges in deploying the solution in real-world settings and study approximation opportunities. We experimentally demonstrate MaMoRL's effectiveness on multiple real-world and synthetic grids, as well as for transfer learning. MaMoRL is deployed for use by the Naval Research Laboratory - Marine Meteorology Division (NRL-MMD), Monterey, CA.

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Cited By

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  • (2023)Human-AI Complex Task Planning2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00382(3923-3927)Online publication date: Apr-2023
  • (2023)Port Arrival Reservation System Using Auctions for Fuel Consumption Reduction2023 IEEE International Conference on Big Data (BigData)10.1109/BigData59044.2023.10386620(3212-3221)Online publication date: 15-Dec-2023
  • (2023)SafeWay: Improving the safety of autonomous waypoint detection in maritime using transformer and interpolationMaritime Transport Research10.1016/j.martra.2023.1000864(100086)Online publication date: Jun-2023

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  1. Cooperative Route Planning Framework for Multiple Distributed Assets in Maritime Applications

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    cover image ACM Conferences
    SIGMOD '22: Proceedings of the 2022 International Conference on Management of Data
    June 2022
    2597 pages
    ISBN:9781450392495
    DOI:10.1145/3514221
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 11 June 2022

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    Author Tags

    1. data management for ai
    2. function approximation
    3. multi-agent reinforcement learning
    4. route planning
    5. scalable solution design

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    View all
    • (2023)Human-AI Complex Task Planning2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00382(3923-3927)Online publication date: Apr-2023
    • (2023)Port Arrival Reservation System Using Auctions for Fuel Consumption Reduction2023 IEEE International Conference on Big Data (BigData)10.1109/BigData59044.2023.10386620(3212-3221)Online publication date: 15-Dec-2023
    • (2023)SafeWay: Improving the safety of autonomous waypoint detection in maritime using transformer and interpolationMaritime Transport Research10.1016/j.martra.2023.1000864(100086)Online publication date: Jun-2023

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