Abstract
Formation control (FC) of multi-agent systems plays a critical role in a wide variety of fields. In the absence of absolute positioning, agents in FC systems rely on relative position measurements with respect to their neighbors. In distributed filter design literature, relative observation models are comparatively unexplored, and in FC literature, uncertainty models are rarely considered. In this article, we aim to bridge the gap between these domains, by exploring distributed filters tailored for relative FC of swarms. We propose statistically robust data models for tracking relative positions of agents in a FC network, and subsequently propose optimal Kalman filters for both centralized and distributed scenarios. Our simulations highlight the benefits of these estimators, and we identify future research directions based on our proposed framework.
Original language | English |
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Title of host publication | 30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings |
Publisher | European Signal Processing Conference, EUSIPCO |
Pages | 1422-1426 |
Number of pages | 5 |
ISBN (Electronic) | 9789082797091 |
Publication status | Published - 2022 |
Event | 30th European Signal Processing Conference, EUSIPCO 2022 - Belgrade, Serbia Duration: 29 Aug 2022 → 2 Sept 2022 |
Publication series
Name | European Signal Processing Conference |
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Volume | 2022-August |
ISSN (Print) | 2219-5491 |
Conference
Conference | 30th European Signal Processing Conference, EUSIPCO 2022 |
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Country/Territory | Serbia |
City | Belgrade |
Period | 29/08/22 → 2/09/22 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Keywords
- distributed estimation
- formation control
- Kalman filter
- multi-agent systems
- relative navigation