Decentralized Density Control of Multi-Robot Systems Using PDE-Constrained Optimization

In this letter, we propose a decentralized optimal density control strategy for multi-robot systems modeled as interacting Brownian particles. The robots' density dynamics are described by the Fokker-Planck equation, and an optimal control problem is formulated and solved accordingly. The stability of the decentralized controller is mathematically proven, and validated through simulations and experiments with a team of real brushbots. The results confirm the convergence of the proposed density-based decentralized optimal controller.

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Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2025-03-05
DOI
https://doi.org/10.1109/lra.2025.3548501
Citations
1
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
1.21
Controls
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article

Decentralized Density Control of Multi-Robot Systems Using PDE-Constrained Optimization

L.X. Niu, Gennaro Notomista
1 citations
IEEE Robotics and Automation Letters
Advanced Control Systems Optimization
1.21
article

Decentralized Density Control of Multi-Robot Systems Using PDE-Constrained Optimization

L.X. Niu, Gennaro Notomista
article en
1 citations

Abstract

In this letter, we propose a decentralized optimal density control strategy for multi-robot systems modeled as interacting Brownian particles. The robots' density dynamics are described by the Fokker-Planck equation, and an optimal control problem is formulated and solved accordingly. The stability of the decentralized controller is mathematically proven, and validated through simulations and experiments with a team of real brushbots. The results confirm the convergence of the proposed density-based decentralized optimal controller.

IEEE Robotics and Automation LettersVol. 10(4)
University of Waterloo (CA)
Openalex Percentile: Top 24%
Advanced Control Systems Optimization
1.21
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