A Bid-Based Grouping Method for Communication-Efficient Decentralized Multi-UAV Task Allocation

Kim, Keum-Seong; Kim, Hoyeon; Choi, Han‐Lim

doi:10.1007/s42405-019-00205-1

Cited by 35 publications

(18 citation statements)

References 29 publications

(45 reference statements)

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“…The recent approaches found include improvements of the PI (performance impact) algorithm, like PI-MaxAss [14] and [35]. Moreover, other techniques are improvements of the CBBA algorithm, like modified CCBBA [38], G-CBBA [40] and [41].…”

Section: A Auction Based Algorithmsmentioning

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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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: A Auction Based Algorithmsmentioning

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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“…As the distribution result is related to the internal mechanism of the algorithm, the quality of the solution is difficult to guarantee and evaluate. The common methods based on market mechanisms mainly include the auction algorithm [27,28] and contract net protocol (CNP) [29] .…”

Section: Algorithm Based On Market Mechanismsmentioning

confidence: 99%

Review of Dynamic Task Allocation Methods for UAV Swarms Oriented to Ground Targets

Peng¹,

Wu²,

Xue³

2021

Complex Syst. Model. Simul.

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Dynamic task allocation of unmanned aerial vehicle swarms for ground targets is an important part of unmanned aerial vehicle (UAV) swarms task planning and the key technology to improve autonomy. The realization of dynamic task allocation in UAV swarms for ground targets is very difficult because of the large uncertainty of swarms, the target and environment state, and the high real-time allocation requirements. Hence, dynamic task allocation of UAV swarms oriented to ground targets has become a key and difficult problem in the field of mission planning. In this work, a dynamic task allocation method for UAV swarms oriented to ground targets is comprehensively and systematically summarized from two aspects: the establishment of an allocation model and the solution of the allocation model. First, the basic concept and trigger scenario are introduced.Second, the research status and the advantages and disadvantages of the two allocation models are analyzed.Third, the research status and the advantages and disadvantages of several common dynamic task allocation algorithms, such as the algorithm based on market mechanisms, intelligent optimization algorithm, and clustering algorithm, are evaluated. Finally, the specific problems of the current UAV swarm dynamic task allocation method for ground targets are highlighted, and future research directions are established. This work offers important reference significance for fully understanding the current situation of UAV swarm dynamic task allocation technology.

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“…In addition, Yang et al [17] applied reinforcement learning in the task allocation for UAVs, they designed a networking scheme based on the expansion strategy, based on which the UAVs can improve the assigning through autonomous learning, and they conducted experiments on the UAV swarm to obtain optimized assigning in specific cases. Besides, many other algorithms such as sequential auctions [18], the human-agent collaboration method [19], and the bid-based grouping method 2 Complexity [20] are used.…”

Section: Related Workmentioning

confidence: 99%

NECTAR-An Agent-Based Dynamic Task Allocation Algorithm in the UAV Swarm

et al. 2020

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The advancement of UAV technology makes the use of UAVs more and more widespread, and the swarm is the main mode of UAV applications owing to its robustness and adaptability. Meanwhile, task allocation plays an essential role in a swarm to obtain overall high performance and unleash the potential of each UAVs owing to the complexity of the large-scale swarm. In this paper, we pay attention to the real-time allocation problem of dynamic tasks. We design models for the task assigning problem to construct the constraints model and assigning objectives. In addition, we introduce a novel agent-based allocating mechanism based on the auction process, including the design for three kinds of agents and the cooperation mechanism among different agents. Moreover, we proposed a new algorithm to calculate the bidding values of UAVs, by which the messages passed between UAVs can be reduced. On the basis of the assigning mechanism, we put up with a novel agent-based real-time task allocation algorithm named NECTAR for dynamic tasks in the UAV swarm. Furthermore, we conduct extensive experiments to evaluate the performance of our NECTAR, and the results indicate that NECTAR is able to solve the real-time task allocation for dynamic tasks and achieve high performance of the UAV swarm.

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A Bid-Based Grouping Method for Communication-Efficient Decentralized Multi-UAV Task Allocation

Cited by 35 publications

References 29 publications

A survey of task allocation techniques in MAS

A survey of task allocation techniques in MAS

Review of Dynamic Task Allocation Methods for UAV Swarms Oriented to Ground Targets

NECTAR-An Agent-Based Dynamic Task Allocation Algorithm in the UAV Swarm

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