Decentralized task allocation for heterogeneous teams with cooperation constraints

Choi, Han‐Lim; Whitten, Andrew K.; How, Jonathan P.

doi:10.1109/acc.2010.5530496

Cited by 34 publications

(8 citation statements)

References 14 publications

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“…Substituting Equation (19) into Equation (20), Equation ( 20) can be further simplified as follows: max…”

Section: Minimum Optimization Performance Of Mtcbaamentioning

confidence: 99%

“…The CBAA and CBBA do not have any special requirements for network topology but cannot achieve accurate multi-agent single-target assignment. In 2010, Choi et al [19] addressed the problem of accurate multi-agent single-target assignment through task decomposition, modifying the gain calculation method and task elimination mechanism, and proposed an enhanced algorithm based on the CBBA, which can achieve heterogeneous multi-agent collaboration to accomplish a common task. However, this algorithm can assign at most two agents to the same task at a time.…”

Section: Introductionmentioning

confidence: 99%

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A Multi-Target Consensus-Based Auction Algorithm for Distributed Target Assignment in Cooperative Beyond-Visual-Range Air Combat

Lyu

Dai

et al. 2022

Aerospace

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With recent advances in airborne weapons, air combat tends to occur in the form of beyond-visual-range (BVR) combat and multi-aircraft cooperation. Target assignment is critical in multi-aircraft BVR air combat decision-making. Most previous research on target assignment for multi-aircraft cooperative BVR air combat has focused on centralized algorithms, which can be time-consuming and unreliable. This paper proposes an efficient distributed target assignment algorithm called the multi-target consensus-based auction algorithm (MTCBAA). First, by analyzing the main geometric aspects of BVR air combat, a target assignment model for cooperative BVR air combat was established. Next, based on a consensus-based auction algorithm (CBAA), the MTCBAA was developed to solve the target assignment problem by introducing a cooperative decision-making variable. Although the MTCBAA is based on a greedy mechanism, it can guarantee at least 50% global optimization performance, which was proven through a demonstration of the minimum optimization performance of a centralized target assignment algorithm, since the centralized algorithm is equivalent to the MTCBAA. Finally, experiments were conducted, including an experiment that illustrates the operation of the proposed algorithm, Monte Carlo comparisons with a centralized target assignment method based on the immune algorithm, and deployment experiments on a semi-physical simulation platform. Compared with the heuristic target assignment algorithm, the proposed algorithm significantly improved the target assignment efficiency. The practicality of the proposed algorithm was further verified through a distributed semi-physical simulation experiment.

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“…Substituting Equation (19) into Equation (20), Equation ( 20) can be further simplified as follows: max…”

Section: Minimum Optimization Performance Of Mtcbaamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Multi-Target Consensus-Based Auction Algorithm for Distributed Target Assignment in Cooperative Beyond-Visual-Range Air Combat

Lyu

Dai

et al. 2022

Aerospace

View full text Add to dashboard Cite

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Section: Decentralized Coordination Approachesmentioning

confidence: 99%

“…The CBBA has also been extended to consider coupled constraints [87,88]. Choi et al in [87] extended CBBA for heterogeneous task allocation to UAV agents with different qualifications and various cooperation constraints. The CBBA was extended with task decomposition and a scoring modification to allow for soft-constraints related with cooperation preferences and a decentralized task elimination protocol that ensures satisfaction of the hard-constraints related with cooperation requirements.…”

Section: Decentralized Coordination Approachesmentioning

confidence: 99%

Decentralizing Coordination in Open Vehicle Fleets for Scalable and Dynamic Task Allocation

et al. 2020

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One of the major challenges in the coordination of large, open, collaborative, and commercial vehicle fleets is dynamic task allocation. Self-concerned individually rational vehicle drivers have both local and global objectives, which require coordination using some fair and efficient task allocation method. In this paper, we review the literature on scalable and dynamic task allocation focusing on deterministic and dynamic two-dimensional linear assignment problems. We focus on multiagent system representation of open vehicle fleets where dynamically appearing vehicles are represented by software agents that should be allocated to a set of dynamically appearing tasks. We give a comparison and critical analysis of recent research results focusing on centralized, distributed, and decentralized solution approaches. Moreover, we propose mathematical models for dynamic versions of the following assignment problems well known in combinatorial optimization: the assignment problem, bottleneck assignment problem, fair matching problem, dynamic minimum deviation assignment problem, Σk-assignment problem, the semiassignment problem, the assignment problem with side constraints, and the assignment problem while recognizing agent qualification; all while considering the main aspect of open vehicle fleets: random arrival of tasks and vehicles (agents) that may become available after assisting previous tasks or by participating in the fleet at times based on individual interest.

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“…At present, numerous versions of CBBA have been proposed from different perspectives. Decentralized methods for allocating heterogeneous tasks to a network of agents with different capabilities are presented in [8], which increases the cooperation constraints of robots and proposes a new scoring mechanism. A new auction and consensus based algorithm for fast task allocation in parallel with task execution is proposed.…”

mentioning

confidence: 99%

Research on Collaborative Task Allocation of Heterogeneous UAVs With Complex Constraints

Yan,

Xia

2023

IEEE Access

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This paper addresses the multi-task allocation problem with complex constraints in the multi-UAV system by presenting an extension to consensus-based bundle algorithm(CBBA). The presented algorithm termed dynamic clustering consensus-based bundle algorithm(DCCBBA) provides an improved bundle construction, a novel consensus strategy and a systematic way of grouping. DCCBBA features different consensus methods for inner conflict resolution and outer conflict resolution. The inner conflict resolution aims at handling the violated task assignment that belongs to the same cluster, while outer conflict resolution guarantees conflict-free assignments in the overall UAVs. The proposed DCCBBA coupled with Pythagorean Hodograph curves can significantly reduce the number of communication events required to achieve consensus while preserving the robust convergence property of the baseline CBBA. Numerical simulations on various cooperative reconnaissance and strike tasks demonstrate the reduction of communication events compared with the baseline CBBA, the cluster-formed CBBA, the grouped CBBA and Two-layer CBBA.

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Decentralized task allocation for heterogeneous teams with cooperation constraints

Cited by 34 publications

References 14 publications

A Multi-Target Consensus-Based Auction Algorithm for Distributed Target Assignment in Cooperative Beyond-Visual-Range Air Combat

A Multi-Target Consensus-Based Auction Algorithm for Distributed Target Assignment in Cooperative Beyond-Visual-Range Air Combat

Decentralizing Coordination in Open Vehicle Fleets for Scalable and Dynamic Task Allocation

Research on Collaborative Task Allocation of Heterogeneous UAVs With Complex Constraints

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