Heuristics-Based Multi-Agent Task Allocation for Resilient Operations

Gregory, Jason M.; Al-Hussaini, Sarah; Gupta, Satyandra K.

doi:10.1109/ssrr.2019.8848939

Cited by 5 publications

(3 citation statements)

References 23 publications

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“…[97] [98]. According to previous research, reliability should be taken into consideration a priory, because by neglecting the possibility of failure, the performance decreases (suboptimal performance) [99]. For example, in [100] the authors found that the usage of the Asynchronous Consensus Based Bundle Algorithm (ACBBA) in environments with uncertainty in the communication procedure (realistic lossy network environment), creates inefficient task assignments, especially for a large number of agents.…”

Section: Uncertaintymentioning

confidence: 99%

“…In [99] is studied the problem of uncertainty (generally failure of elements of the task allocation procedure) in multiagent systems, using a heuristic approach and non Markovian states. Their conclusion is that making simplifying assumptions such as Markovian states can lead to results that are not a fair representation of the systems' performance.…”

Section: Uncertaintymentioning

confidence: 99%

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A survey of task allocation techniques in MAS

Skaltsis

Shin

Tsourdos

2021

2021 International Conference on Unmanned Aircraft Systems (ICUAS)

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Multi-agent systems and especially unmanned vehicles, are a crucial part of the solution to a lot of real world problems, making essential the improvement of task allocation techniques. In this review, we present the main techniques used for task allocation algorithms, categorising them based on the techniques used, focusing mainly on recent works. We also analyse these methods, focusing mainly on their complexity, optimality and scalability. We also refer to common communication schemes used in task allocation methods, as well as to the role of uncertainty in task allocation. Finally, we compare them based on the above criteria, trying to find gaps in the literature and to propose the most promising ones.

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Section: Uncertaintymentioning

confidence: 99%

Section: Uncertaintymentioning

confidence: 99%

A survey of task allocation techniques in MAS

Skaltsis

Shin

Tsourdos

2021

2021 International Conference on Unmanned Aircraft Systems (ICUAS)

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show abstract

“…The transportation task allocation problem has been resolved in a multi-robot system with collision avoidance through the use of table working approach [19]. The task allocation among multiple mobile robots has been accomplished using non-markovian modeling of states [20].…”

Section: Introductionmentioning

confidence: 99%

Cooperative Path Planning for Object Transportation with Fault Management

Sindhuja

Sahu

Das

et al. 2023

Preprint

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The current research intents on enhancing the service ability of mobile robot by cooperative path planning. The strategy is developed by fusion of sine cosine algorithm and particle swarm optimization approach for the transition of service robot in complex environment. To ensure the successful execution of the intended task it is essential to have a faultless and collision-less path for the mobile robot. This supposition can be achieved by producing an intelligent fault-managed approach. The proposed paper addresses the object transportation by a pair of robots from source to destination, this task can be accomplished in three step, such as fault identification, fault resolution using robot replacement and computation of a collision-less path. At each step of transition, path planning is carried out to reach the target location. Sine cosine algorithm improves the exploration capability of the robots in the multi robot environment. Particle swarm optimization being the simplest technique to exercise the path planning problem produces an optimal global position for each particle along each dimension. The fusion of both provides a balance exploration-exploitation ability of the mobile robot. Fault identification overcomes the faulty transition and unsuccessful transition of the robot by detecting the fault of any robot through its non-responding time. K- nearest neighbor approach identifies the nearest working robot to replace the faulty on. The algorithm has been exercised in C language to showcase its capability in terms of execution time, path traveled, path deviated etc. The comparative analysis proofs the supremacy of the proposed algorithm in terms of several metrics such as path planning, cooperation, fault management, etc.

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A Review of Task Allocation Methods for UAVs

Skaltsis,

Shin,

Tsourdos

2023

J Intell Robot Syst

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Unmanned aerial vehicles, can offer solutions to a lot of problems, making it crucial to research more and improve the task allocation methods used. In this survey, the main approaches used for task allocation in applications involving UAVs are presented as well as the most common applications of UAVs that require the application of task allocation methods. They are followed by the categories of the task allocation algorithms used, with the main focus being on more recent works. Our analysis of these methods focuses primarily on their complexity, optimality, and scalability. Additionally, the communication schemes commonly utilized are presented, as well as the impact of uncertainty on task allocation of UAVs. Finally, these methods are compared based on the aforementioned criteria, suggesting the most promising approaches.

show abstract

Heuristics-Based Multi-Agent Task Allocation for Resilient Operations

Cited by 5 publications

References 23 publications

A survey of task allocation techniques in MAS

A survey of task allocation techniques in MAS

Cooperative Path Planning for Object Transportation with Fault Management

A Review of Task Allocation Methods for UAVs

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