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    Evaluating Tradeoffs for Swarm Reconnaissance With Autonomous Ground Vehicles

    Source: Journal of Autonomous Vehicles and Systems:;2022:;volume( 002 ):;issue: 001::page 11002
    Author:
    Goodin, Christopher;Cagle, Lucas;Henley, Greg;Fereday, Rhett;Carrillo, Justin;Song, Peilin;McInnis, David
    DOI: 10.1115/1.4054581
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Autonomous ground vehicles (AGVs) operating collaboratively have several advantages over vehicles operating alone. An AGV team may be more resilient and efficient than a single AGV. Other advantages of AGV teams include increased coverage and multiple viewing angles of terrain features as well as resistance to failure from any single AGV. Additionally, AGV teams can explore large terrains more quickly and thoroughly than a single system. In this work, the feasibility of using a team of high-mobility AGV to explore a navigation corridor, map the terrain, and autonomously flag obstacles for future navigation is evaluated. Focusing on negative obstacles, the value of using multiple vehicles to map a navigation corridor is quantified. This study is the first to evaluate large teams of AGV collaborating in realistic off-road, 3D environments. The feasibility of the large-scale AGV team is demonstrated while avoiding the high cost of purchasing and testing large numbers of vehicles using the Mississippi State University autonomous vehicle simulator (MAVS), a high-fidelity, physics-based simulation tool. The cost and benefits of increasing the AGV team size are evaluated. The simulation results show how factors like fuel use, map coverage, and obstacle detection are influenced by increasing numbers of AGV in the team. The simulation architecture is presented and experiments quantifying the performance of the simulator are shown. Finally, a model for evaluating the tradeoff between mission effectiveness and fuel use is developed and presented to demonstrate the utility of this approach.
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      Evaluating Tradeoffs for Swarm Reconnaissance With Autonomous Ground Vehicles

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    contributor authorGoodin, Christopher;Cagle, Lucas;Henley, Greg;Fereday, Rhett;Carrillo, Justin;Song, Peilin;McInnis, David
    date accessioned2022-12-27T23:12:28Z
    date available2022-12-27T23:12:28Z
    date copyright6/6/2022 12:00:00 AM
    date issued2022
    identifier issn2690-702X
    identifier otherjavs_2_1_011002.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4288112
    description abstractAutonomous ground vehicles (AGVs) operating collaboratively have several advantages over vehicles operating alone. An AGV team may be more resilient and efficient than a single AGV. Other advantages of AGV teams include increased coverage and multiple viewing angles of terrain features as well as resistance to failure from any single AGV. Additionally, AGV teams can explore large terrains more quickly and thoroughly than a single system. In this work, the feasibility of using a team of high-mobility AGV to explore a navigation corridor, map the terrain, and autonomously flag obstacles for future navigation is evaluated. Focusing on negative obstacles, the value of using multiple vehicles to map a navigation corridor is quantified. This study is the first to evaluate large teams of AGV collaborating in realistic off-road, 3D environments. The feasibility of the large-scale AGV team is demonstrated while avoiding the high cost of purchasing and testing large numbers of vehicles using the Mississippi State University autonomous vehicle simulator (MAVS), a high-fidelity, physics-based simulation tool. The cost and benefits of increasing the AGV team size are evaluated. The simulation results show how factors like fuel use, map coverage, and obstacle detection are influenced by increasing numbers of AGV in the team. The simulation architecture is presented and experiments quantifying the performance of the simulator are shown. Finally, a model for evaluating the tradeoff between mission effectiveness and fuel use is developed and presented to demonstrate the utility of this approach.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleEvaluating Tradeoffs for Swarm Reconnaissance With Autonomous Ground Vehicles
    typeJournal Paper
    journal volume2
    journal issue1
    journal titleJournal of Autonomous Vehicles and Systems
    identifier doi10.1115/1.4054581
    journal fristpage11002
    journal lastpage11002_11
    page11
    treeJournal of Autonomous Vehicles and Systems:;2022:;volume( 002 ):;issue: 001
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian