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Adaptive Measurement Selection for Scalable Distributed Graph Optimization in Multi-UAV Relative Positioning Cover

Adaptive Measurement Selection for Scalable Distributed Graph Optimization in Multi-UAV Relative Positioning

Measurement Science Review
Volume 25 (2025): Issue 4 (August 2025)
By: Chengsong Xiong and  Zheng You  
Open Access
|Aug 2025

Figures & Tables

Fig. 1.

Schematic diagram of relative positioning for UAV swarm. (a) Positioning based on external anchors. (b) Anchor-free relative positioning. (c) The influence of formation on positioning accuracy.
Schematic diagram of relative positioning for UAV swarm. (a) Positioning based on external anchors. (b) Anchor-free relative positioning. (c) The influence of formation on positioning accuracy.

Fig. 2.

The DGO scheme for UAV swarm.
The DGO scheme for UAV swarm.

Fig. 3.

UAV swarms used in the simulations. (a) 12-UAV swarm. (b) 24-UAV swarm. (c) 36-UAV swarm. (d) 100-UAV swarm.
UAV swarms used in the simulations. (a) 12-UAV swarm. (b) 24-UAV swarm. (c) 36-UAV swarm. (d) 100-UAV swarm.

Fig. 4.

The flight trajectory of the swarm.
The flight trajectory of the swarm.

Fig. 5.

Relative positioning error variations with respect to No across four methods. (a) Error curves for the 12-UAV swarm. (b) Error curves for the 24-UAV swarm. (c) Error curves for the 36-UAV swarm. (d) Error curves for the 100-UAV swarm.
Relative positioning error variations with respect to No across four methods. (a) Error curves for the 12-UAV swarm. (b) Error curves for the 24-UAV swarm. (c) Error curves for the 36-UAV swarm. (d) Error curves for the 100-UAV swarm.

Fig. 6.

The variation of computation time per step with No.
The variation of computation time per step with No.

Fig. 7.

Relative positioning error for four methods in the 100-UAV swarm under different sensing conditions. (a) No = 4. (b) No = 6. (c) No = 8. (d) No = 10.
Relative positioning error for four methods in the 100-UAV swarm under different sensing conditions. (a) No = 4. (b) No = 6. (c) No = 8. (d) No = 10.

Fig. 8.

Dynamic formation reconfiguration. (a) Transformation from rectangle formation to circular formation. (b) Transformation from circular formation to V-formation.
Dynamic formation reconfiguration. (a) Transformation from rectangle formation to circular formation. (b) Transformation from circular formation to V-formation.

Fig. 9.

Error curves in topology reconfiguration simulation.
Error curves in topology reconfiguration simulation.

The statistical metrics of the relative positioning methods_

MethodMAE (m)STD (m)MAX (m)
State estimation1.6050.3652.606
CGO0.7180.2001.276
DF0.8180.1791.286
Fi-max0.8030.2061.410
Fi-random0.7200.2131.340
Fi-min0.5990.1691.163
DOI: https://doi.org/10.2478/msr-2025-0023 | Journal eISSN: 1335-8871
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Language: English
Page range: 190 - 199
Submitted on: Mar 2, 2025
|
Accepted on: Jul 25, 2025
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Published on: Aug 28, 2025
Published by: Slovak Academy of Sciences, Institute of Measurement Science
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
UAV swarm,
distributed graph optimization,
Fisher Information Matrix,
optimal measurement constraint
Related subjects:
Engineering,
Electrical engineering,
Control engineering, metrology and testing

© 2025 Chengsong Xiong, Zheng You, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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