Optimization-based control for Multi-Agent deployment via dynamic Voronoi partition

Nguyen, Minh Tri; Maniu, Cristina Stoica; Olaru, Sorin

doi:10.1016/j.ifacol.2017.08.185

Cited by 10 publications

(23 citation statements)

References 27 publications

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“…In [Bullo et al, 2009] this is referred to as an open research question. This conjectured property is supported by simulations in [Nguyen et al, 2017;Bullo et al, 2009;.…”

Section: Introductionsupporting

confidence: 58%

“…u. Proving convergence to a Chebyshev configuration for discrete time MAS was thought to be solved by a result in [Nguyen et al, 2017]. In the prequel to the present thesis, the report [Hatleskog, 2017], said result came under scrutiny.…”

Section: Contributionsmentioning

confidence: 90%

“…The frameworks presented in Nguyen et al [2017] and are related by virtue of exploiting the same target point. Meanwhile they differ in the sense that the former paper i) considers discrete time dynamics, ii) accommodates a larger class of heterogeneous agent dynamics and iii) allows for deployment to both the plane as well as R d for any finite d t1, 2, .…”

Section: Contributionsmentioning

confidence: 99%

“…In this manuscript we consider the discrete time Voronoi-based framework in [Nguyen et al, 2017], this case being closer to a practical application where the control actions are computed in at a regularly spaced interval. The authors use the Chebyshev center of a cell, the center of an inscribed Euclidean ball of maximal radius, as the target.…”

Section: Introductionmentioning

confidence: 99%

“…However, proving convergence to a local optimum of the sphere packing multi-center function is not sufficient to establish stationarity. A necessary step in ensuring convergence to a static configuration is showing convergence to a so-called Chebyshev configuration [Nguyen et al, 2017]. The MAS is in a Chebyshev configuration when all agents are at a Chebyshev center of their respective Voronoi cells.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Voronoi-Based Deployment of Multi-Agent Systems

Hatleskog

Olaru

Hovd

2018

2018 IEEE Conference on Decision and Control (CDC)

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This thesis investigates convergence in the framework of Voronoi-based deployment of a multi-agent system to a convex polytopic multi-dimensional environment. The deployment objective is to drive the system into a stable static configuration which exhibits optimal coverage of the target environment. To this end, the system is subjected to a collection of decentralized control laws steering each agent towards a Chebyshev center of its associated time-varying polytopic Voronoi-neighborhood. In non-degenerate cases, socalled Chebyshev configurations of the multi-agent system achieves the above objective. In these configurations, all agents are at a Chebyshev center of their Voronoi-neighborhood. Proving convergence to the set of Chebyshev configurations is an open research question. This is the most pertinent issue with regards to the framework viability. While such a property is supported by simulations, neither complete formal convergence proofs nor formal characterizations of the equilibria to be achieved exist. This thesis is oriented towards strengthening the theoretical convergence results. For the special case of deployment to one-dimensional environments, we prove convergence to an unique static Chebyshev configuration. Moreover, we highlight connections to discrete time averaging systems and show how the system converges to consensus on the Chebyshev radii. The remaining results apply in the general case of multi-dimensional environments. We introduce a novel undirected interaction graph as a theoretical tool for a deeper understanding of the multi-agent system's functioning. Exploiting this graph, we prove that the set of static configurations are Chebyshev configurations in which all subsets of agents within the same connected component of the interaction graph are in consensus on their Chebyshev radii. Finally we prove convergence to a Chebyshev configuration, with consensus on the Chebyshev radii, provided the interaction graph is connected along the trajectories of the multi-agent system. Throughout the presentation, the theoretical results are motivated and supported by simulations.

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“…In [Bullo et al, 2009] this is referred to as an open research question. This conjectured property is supported by simulations in [Nguyen et al, 2017;Bullo et al, 2009;.…”

Section: Introductionsupporting

confidence: 58%

Section: Contributionsmentioning

confidence: 90%

Section: Contributionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Voronoi-Based Deployment of Multi-Agent Systems

Hatleskog

Olaru

Hovd

2018

2018 IEEE Conference on Decision and Control (CDC)

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Decentralized MPC for UAVs Formation Deployment and Reconfiguration with Multiple Outgoing Agents

Chevet¹,

Vlad²,

Maniu³

et al. 2019

J Intell Robot Syst

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This paper presents a new decentralized algorithm for the deployment and reconfiguration of a multi-agent formation in a convex bounded polygonal area when considering several outgoing agents. The system is deployed over a twodimensional convex bounded area, each agent being driven by its own linear model predictive controller. At each time instant, the area is partitioned into Voronoi cells associated with each agent. Due to the movement of the agents, this partition is time-varying. The objective of the proposed algorithm is to drive the agents into a static configuration based on the Chebyshev center of each Voronoi cell. When some This work was supported by the CNRS' LIA on Information, Learning and Control and the Natural Sciences and Engineering Research Council of Canada.

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Estimation of multiple crack propagation pattern in concrete using Voronoi tessellation method

Bayar,

Bilir

2023

Sādhanā

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Optimization-based control for Multi-Agent deployment via dynamic Voronoi partition

Cited by 10 publications

References 27 publications

Voronoi-Based Deployment of Multi-Agent Systems

Voronoi-Based Deployment of Multi-Agent Systems

Decentralized MPC for UAVs Formation Deployment and Reconfiguration with Multiple Outgoing Agents

Estimation of multiple crack propagation pattern in concrete using Voronoi tessellation method

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