A Correlated Random Walk Model to Rapidly Approximate Hitting Time Distributions in Multi-robot Systems

Zhang, Yi; Boley, Daniel; Harwell, John; Gini, Maria

doi:10.1007/978-3-031-22216-0_48

Cited by 1 publication

(2 citation statements)

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“…Task coordination for optimal multi-robot evolution through a task-based multi-robot task allocation (MRTA) optimal assignment problem (OAP) is emphasized by Gerkey and Matarić [9]. Additionally, Lee et al [10] focus on developing a metric for estimating fault levels within a swarm of robots, while Zhang et al [11] introduce a model based on data correlation, specifically the correlated random walk model, to efficiently approximate task searching time for distributions of multi-robot systems in large arenas.…”

Section: Introductionmentioning

confidence: 99%

“…We introduce Fcon/AP as the reduced effective availability of at least one link with a predefined access point. If F con ref represents the reference threshold for a Wi-Fi connection to an access point and Fcon(t) signifies the current connectivity level of an agent to the access point, then Fcon/AP is defined as the ratio of the instant connectivity Fcon(t) to the reference threshold F con ref This is expressed as (11):…”

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confidence: 99%

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Distributed and autonomous multi-robot for task allocation and collaboration using a greedy algorithm and robot operating system platform

Tamali,

Amardjia,

Tamali

2024

IJRA

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Research investigations in the realm of micro-robotics often center around strategies addressing the multi-robot task allocation (MRTA) problem. Our contribution delves into the collaborative dynamics of micro-robots deployed in targeted hostile environments. Employing advanced algorithms, these robots play a crucial role in enhancing and streamlining operations within sensitive areas. We adopt a tailored GREEDY approach, strategically adjusting weight parameters in a multi-objective function that serves as a cost metric. The objective function, designed for optimization purposes, aggregates the cost functions of all agents involved. Our evaluation meticulously examines the MRTA efficiency for each micro-robot, considering dependencies on factors such as radio connectivity, available energy, and the absolute and relative availability of agents. The central focus is on validating the positive trend associated with an increasing number of agents constituting the cluster. Our methodology introduces a trio of micro-robots, unveiling a flexible strategy aimed at detecting individuals at risk in demanding environments. Each micro-robot within the cluster is equipped with logic that ensures compatibility and cooperation, enabling them to effectively execute assigned missions. The implementation of MRTA-based collaboration algorithms serves as an adaptive strategy, optimizing agents' mobility based on specific criteria related to the characteristics of the target site.<p class="JAMRISAbstract"> </p>

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%