Distributed Non-Uniform Scaling Control of Multi-Agent Formation with Dynamic Agent Joining

Fuente: arXiv
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Auteurs principaux: He, Tao, Jing, Gangshan
Format: Preprint
Publié: 2026
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author He, Tao
Jing, Gangshan
author_facet He, Tao
Jing, Gangshan
contents Non-uniform scaling control of formation enables multi-agent systems to adjust their shape by scaling with different ratios along different coordinate axes, offering enhanced flexibility in complex environments. However, like most existing formation maneuver strategies, it typically assumes a fixed set of agents, limiting its applicability in scenarios requiring dynamic team expansion. This paper introduces a distributed control framework that enables a formation to incorporate new agents during non-uniform scaling maneuvers in arbitrary dimensions while preserving the spectral properties of the graph Laplacian. Simulation examples validate the effectiveness of the theoretical results.
format Preprint
id arxiv_https___arxiv_org_abs_2605_29191
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Distributed Non-Uniform Scaling Control of Multi-Agent Formation with Dynamic Agent Joining
He, Tao
Jing, Gangshan
Systems and Control
Robotics
Optimization and Control
Non-uniform scaling control of formation enables multi-agent systems to adjust their shape by scaling with different ratios along different coordinate axes, offering enhanced flexibility in complex environments. However, like most existing formation maneuver strategies, it typically assumes a fixed set of agents, limiting its applicability in scenarios requiring dynamic team expansion. This paper introduces a distributed control framework that enables a formation to incorporate new agents during non-uniform scaling maneuvers in arbitrary dimensions while preserving the spectral properties of the graph Laplacian. Simulation examples validate the effectiveness of the theoretical results.
title Distributed Non-Uniform Scaling Control of Multi-Agent Formation with Dynamic Agent Joining
topic Systems and Control
Robotics
Optimization and Control
url https://arxiv.org/abs/2605.29191