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Cited by 23Distributed Control Multi-Agent SystemsModular Robots and Swarm IntelligenceRobotic Path Planning Algorithms

The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.

Distributed Progressive Formation Control for Multi-Agent Systems: 2D and 3D deployment of UAVs in ROS/Gazebo with RotorS

McCord, Cassandra, Queralta, Jorge Pena, Gia, Tuan Nguyen, Westerlund, Tomi·2019·2019 European Conference on Mobile Robots (ECMR)
DOI 10.1109/ecmr.2019.8870934
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Abstract

Coordination of multiple robots in order to cooperatively perform a given task requires a certain distribution of the different units in space. Furthermore, individual robots, or agents, might have different tasks, or positions, assigned. Formation control algorithms might rely on a priori information, a centralized controller, or communication among the agents to assign roles. Distributed approaches that only need local interaction between agents have limited possibilities, such as flocks where agents actively control the distance to neighboring agents. Alternatively, two-way local communication has been applied to progressively assign roles and converge towards a given configuration. We propose a progressive assignment algorithm and formation control scheme that extends leader-follower formations in order to enable cooperation of multiple robots with minimal, one-way, local communication between agents. The proposed algorithm progressively generates a directed, locally convex, path graph to uniquely assign formation positions to all agents. The low computational complexity of our algorithm enables its implementation in resource-limited devices. Agents only require information about neighboring agents and be able to locally broadcast their status. This algorithm enables almost arbitrary two-dimensional configurations, with the only limitation being the sensing range enabling the definition of a series of convex hulls in a certain subset of agents such that agents sharing an edge in the hull are able to sense each other. Moreover, we propose a methodology for deploying agents to an arbitrary three-dimensional configuration after the assignment process is made on the plane.

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Crossref · 10.1109/ecmr.2019.8870934

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25 of 25 references verified0 citation errors · 0 not checkable

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Research works printed but not linked: 2

  1. furrer, 2016, Robot Operating System (ROS): The Complete Reference, Ch RotorS-A Modular Gazebo MAV Simulator Framework, 1
  2. 10.1109/IROS.2014.6943105 · DOI

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Metadata

Authors
McCord, C., Queralta, J. P., Gia, T. N., & Westerlund, T.
Affiliations
University of Turku (FI)
ORCID
Venue
2019 European Conference on Mobile Robots (ECMR)
Publisher
IEEE
Published
2019-09
Pages
1-6
DOI
10.1109/ecmr.2019.8870934
OpenAlex
W2981011740
Cited by
23
References
25
Citations by year
2025: 2 · 2024: 1 · 2023: 4 · 2022: 4 · 2021: 2 · 2020: 8 · 2019: 2
FWCI
3.46
Type
conference paper
Language
en
Open access
closed
Licence
Locations
European Conference on Mobile Robots (publishedVersion)
Topics
  • Physical Sciences › Engineering › Control and Systems Engineering › Distributed Control Multi-Agent Systems
  • Physical Sciences › Engineering › Mechanical Engineering › Modular Robots and Swarm Intelligence
  • Physical Sciences › Engineering › Control and Systems Engineering › Robotic Path Planning Algorithms
Keywords
formation control, multi-agent systems, UAV deployment, leader-follower formation, distributed control, convex hull, path graphs, ROS-Gazebo simulation, rotor

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