Skip to Main content Skip to Navigation
Journal articles

Chance-Constrained MPC for Voronoi-based Multi-Agent System Deployment

Abstract : This paper proposes a new chance-constrained model predictive control (CCMPC) algorithm with state estimation applied to the two-dimensional deployment of a multi-vehicle system where each agent is subject to process noise and measurement noise. The bounded convex area of deployment is partitioned into time-varying Voronoi cells defined by the position of each agent. Due to the presence of noise in the system model, stochastic constraints appear in the model predictive control problem. The proposed decentralized robust CCMPC algorithm drives the multi-agent system into a static Chebyshev configuration where each agent lies on the Chebyshev center of its Voronoi cell. Simulation results show the effectiveness of the proposed control strategy on a fleet of quadrotors subject to wind perturbations and measurement noise.
Document type :
Journal articles
Complete list of metadata
Contributor : Thomas Chevet <>
Submitted on : Wednesday, May 5, 2021 - 9:59:34 AM
Last modification on : Tuesday, June 22, 2021 - 3:53:00 AM


Chevet et al - IFAC WC 2020.pd...
Files produced by the author(s)


Distributed under a Creative Commons Attribution - NonCommercial - NoDerivatives 4.0 International License



Thomas Chevet, Cristina Stoica Maniu, Cristina Vlad, Youmin Zhang, Eduardo Fernandez Camacho. Chance-Constrained MPC for Voronoi-based Multi-Agent System Deployment. IFAC-PapersOnLine, Elsevier, 2020, 21st IFAC World Congress, 53 (2), pp.6969-6974. ⟨10.1016/j.ifacol.2020.12.417⟩. ⟨hal-02571729⟩



Record views


Files downloads