Multi-robot Task Allocation System: Fuzzy Auction-Based and Adaptive Multi-threshold Approaches

Al-Shaboti, Mohammed; Baroudi, Uthman

doi:10.1007/s42979-021-00479-x

Cited by 6 publications

(2 citation statements)

References 28 publications

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“…For example, Khamis et al [32] studied multi-robot systems executing collective behaviors for tackling complex tasks. Similarly, Alshaboti and Baroudi [33] discussed state-of-the-art algorithms and strategies employed in tackling MRTA problems, providing insights into the evolving landscape of robot task allocation. Additionally, Chakraa et al [34] reviewed optimization techniques for multi-robot task allocation problems, showcasing current methods and offering insights into future directions for optimizing task allocation among multi-robots.…”

Section: Task Sequencing: Conceptual Clarifications and Evolutionmentioning

confidence: 99%

Simulation of Heuristics for Automated Guided Vehicle Task Sequencing with Resource Sharing and Dynamic Queues

Leon,

Peyman,

Martin

et al. 2024

Mathematics

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Automated guided vehicles (AGVs) stand out as a paradigmatic application of Industry 4.0, requiring the seamless integration of new concepts and technologies to enhance productivity while reducing labor costs, energy consumption, and emissions. In this context, specific industrial use cases can present a significant technological and scientific challenge. This study was inspired by a real industrial application for which the existing AGV literature did not contain an already well-studied solution. The problem is related to the sequencing of assigned tasks, where the queue formation dynamics and the resource sharing define the scheduling. The combinatorial nature of the problem requires the use of advanced mathematical tools such as heuristics, simulations, or a combination of both. A heuristic procedure was developed that generates candidate task sequences, which are, in turn, evaluated in a discrete-event simulation model developed in Simul8. This combined approach allows high-quality solutions to be generated and realistically evaluated, even graphically, by stakeholders and decision makers. A number of computational experiments were developed to validate the proposed method, which opens up some future lines of research, especially when considering stochastic settings.

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Section: Task Sequencing: Conceptual Clarifications and Evolutionmentioning

confidence: 99%

Simulation of Heuristics for Automated Guided Vehicle Task Sequencing with Resource Sharing and Dynamic Queues

Leon,

Peyman,

Martin

et al. 2024

Mathematics

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“…Alshaboti investigated the performance of two commonly-used approaches, auction-based and threshold-based, in multi-objective dynamic target allocation scenarios. They demonstrated that the auction-based method using a fuzzy inference system outperformed the adaptive threshold-based method in terms of load balancing, while the adaptive threshold-based method achieved better results in terms of travel distance [19]. The main advantage of auction-based methods is their simplicity and the fact that they allow for decentralized application on real robots.…”

Section: Multiple Usvsmentioning

confidence: 99%

A Novel Region-Construction Method for Multi-USV Cooperative Target Allocation in Air–Ocean Integrated Environments

Zhou

Hao

2023

JMSE

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The effective defense of sparsely populated border islands, surrounded by a multifaceted sea, against enemy infiltration poses a crucial problem in national defense. One possible solution is to deploy multiple unmanned surface vessels (USVs) to form an intelligent patrol and defense system. With the designated or daily patrols of USVs, we need to allocate target positions in real time to ensure their continuous operation. Currently, the state-of-art methods contain two major problems of target deadlock and local optimization, which limit the efficiency of reaching the target. To this end, we proposed a novel Region-Construction (RECO) method aimed at high-efficiency target allocation. Firstly, a dynamic calculation approach in K value for unsupervised clustering and time factor’s lead-in for Market-Based Mechanism (MBM) method was created to resolve potential target deadlock among USVs. Secondly, we proposed a novel construction strategy in a non-complete graph (NCG) consisting of neighborhood connection and pheromone extension to provide enough feasible nodes for solution searching. Finally, we introduced adjustment of search range and edge weights, and activated node interaction in traditional Ant Colony Optimization (ACO) algorithm in NCG to obtain the optimal combination of each USV’s target allocations. We established a simulation platform with an airborne managing base station and several USVs. The experimental results demonstrated that when the number of USVs was four, the average time for all USVs to reach the target in the RECO method reduced by 10.9% and 7.7% compared to the MBM and ACO methods, respectively. This reduction was 25% and 11.6% for 6 USVs, 25.7% and 21.8% for 8 USVs, 20% and 19% for 10 USVs. It reflects that the proposed RECO allocation method has shown improvements in terms of successfully-assigned USVs’ quantity and operational efficiency, compared to the state-of-art MBM and ACO algorithms.

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Two-stage task allocation for multiple construction robots using an improved genetic algorithm

Ye,

Guo,

Luo

2024

Automation in Construction

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Multi-robot Task Allocation System: Fuzzy Auction-Based and Adaptive Multi-threshold Approaches

Cited by 6 publications

References 28 publications

Simulation of Heuristics for Automated Guided Vehicle Task Sequencing with Resource Sharing and Dynamic Queues

Simulation of Heuristics for Automated Guided Vehicle Task Sequencing with Resource Sharing and Dynamic Queues

A Novel Region-Construction Method for Multi-USV Cooperative Target Allocation in Air–Ocean Integrated Environments

Two-stage task allocation for multiple construction robots using an improved genetic algorithm

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