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

被引：0

作者：

Niu, Longchen ^{[1
]}

Notomista, Gennaro ^{[1
]}

机构：

[1] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON N2L 3G1, Canada

来源：

IEEE ROBOTICS AND AUTOMATION LETTERS | 2025年 / 10卷 / 04期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Robots; Mathematical models; Noise; Robot sensing systems; Stochastic processes; Optimization; Probability density function; Location awareness; Swarm robotics; Convergence; Distributed robot systems; multi-robot systems; optimization and optimal control;

D O I：

10.1109/LRA.2025.3548501

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

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.

引用

页码：4045 / 4052

页数：8

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