Multi-UAV Decentralized Task Allocation with Intermittent Communications: the DTC algorithm

Dionne, Dany; Rabbath, C.A.

doi:10.1109/acc.2007.4282637

Cited by 27 publications

(10 citation statements)

References 7 publications

(13 reference statements)

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“…This can cause severe latency in low bandwidth environments and can substantially increase the time it takes to find an assignment for the fleet. To resolve this, approaches that do not aim for perfect consensus on the SA have been suggested: the robust decetralized task asslignment (RDTA) algorithm 23 enhanced robustness to inconsistent SA by allowing agents to communicate plans as well as SA, while the decentralized task consensus (DTC) algorithm 24 restricted communication occurrence only to the cases there is mismatch between plans based on the local knowledge and on the estimated global knowledge 24 . However, these algorithms might still take a significant amount of time to produce a final solution, because the first requires each agent to receive plans from all other agents, and the second might still need perfect consensus to guarantee conflict-free solutions.…”

Section: Introductionmentioning

confidence: 99%

Consensus-Based Auction Approaches for Decentralized Task Assignment

Brunet

Choi

How

2008

AIAA Guidance, Navigation and Control Conference and Exhibit

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This paper addresses task assignment in the coordination of a fleet of unmanned vehicles by presenting two decentralized algorithms: consensus-based auction algorithm (CBAA) and its generalization to the multi-assignment problem, consensus-based bundle algorithm (CBBA). These algorithms utilize a market-based decision strategy as the mechanism for decentralized task selection, and use a consensus routine based on local communication as the conflict resolution mechanism by achieving agreement on the winning bid values. The conflict resolution process of CBBA is further enhanced to address the dependency of the score value on the previously selected tasks in the multi-assignment setting. This work shows that the proposed algorithms, under reasonable assumptions on the scoring scheme and network connectivity, guarantee convergence to a conflict-free assignment. Also, the converged solutions are shown to guarantee 50% optimality in the worst-case and to exhibit provably good performance on average. Moreover, the proposed algorithms produce a feasible assignment even in the presence of inconsistency in situational awareness across the fleet, and even when the score functions varies with time in some standard manner. Numerical experiments verify quick convergence and good performance of the presented methods for both static and dynamic assignment problems.

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Section: Introductionmentioning

confidence: 99%

Consensus-Based Auction Approaches for Decentralized Task Assignment

Brunet

Choi

How

2008

AIAA Guidance, Navigation and Control Conference and Exhibit

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“…Among other decentralized techniques, coordination algorithms for task allocation that use only local sensing and no direct communication between robots have been proposed in [23]. Additionally, consensus based approaches that typically require the robots to converge on a consistent situational awareness before performing the assignment have been explored in [24,25,26]. Though such methods are robust, they are typically slow to converge, and require the transmission of large amounts of data.…”

Section: Arxiv:180508712v1 [Cssy] 22 May 2018mentioning

confidence: 99%

A Distributed Version of the Hungarian Method for Multirobot Assignment

et al. 2017

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In this paper, we propose a distributed version of the Hungarian Method to solve the well known assignment problem. In the context of multi-robot applications, all robots cooperatively compute a common assignment that optimizes a given global criterion (e.g. the total distance traveled) within a finite set of local computations and communications over a peer-to-peer network. As a motivating application, we consider a class of multi-robot routing problems with "spatio-temporal" constraints, i.e. spatial targets that require servicing at particular time instants. As a means of demonstrating the theory developed in this paper, the robots cooperatively find online, suboptimal routes by applying an iterative version of the proposed algorithm, in a distributed and dynamic setting. As a concrete experimental test-bed, we provide an interactive "multi-robot orchestral" framework in which a team of robots cooperatively plays a piece of music on a so-called orchestral floor. NOMENCLATUREIn the following table, we present the nomenclature used in this paper. Table of NotationV Vertex partitioning of two disjoint sets R (robots) and P (targets) respectively, denoted by V = (R, P ) E i orig Edge set containing the edges between a robot i ∈ R and every target in P w i orig Weight function corresponding to the edge set E i orig G i orig

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“…Reference [12] investigates the automatic target recognition (ATR) problem in UAV control and proposes a distributed strategy for UAV swarms. Task allocation problem is discussed in [13][14][15][16][17][18] using different methodologies. Some applications of using a UAV swarm to search and destroy targets could be found in [19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Modeling and Flocking Consensus Analysis for Large-Scale UAV Swarms

Huang

2013

Mathematical Problems in Engineering

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Recently, distributed coordination control of the unmanned aerial vehicle (UAV) swarms has been a particularly active topic in intelligent system field. In this paper, through understanding the emergent mechanism of the complex system, further research on the flocking and the dynamic characteristic of UAV swarms will be given. Firstly, this paper analyzes the current researches and existent problems of UAV swarms. Afterwards, by the theory of stochastic process and supplemented variables, a differential-integral model is established, converting the system model into Volterra integral equation. The existence and uniqueness of the solution of the system are discussed. Then the flocking control law is given based on artificial potential with system consensus. At last, we analyze the stability of the proposed flocking control algorithm based on the Lyapunov approach and prove that the system in a limited time can converge to the consensus direction of the velocity. Simulation results are provided to verify the conclusion.

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Multi-UAV Decentralized Task Allocation with Intermittent Communications: the DTC algorithm

Cited by 27 publications

References 7 publications

Consensus-Based Auction Approaches for Decentralized Task Assignment

Consensus-Based Auction Approaches for Decentralized Task Assignment

A Distributed Version of the Hungarian Method for Multirobot Assignment

Modeling and Flocking Consensus Analysis for Large-Scale UAV Swarms

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