Coordination of multiple vessels via distributed nonlinear model predictive control

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Abstract

This work presents a method for multi-robot trajectory planning and coordination based on nonlinear model predictive control (NMPC). In contrast to centralized approaches, we consider the distributed case where each robot has an on-board computation unit to solve a local NMPC problem and can communicate with other robots in its neighborhood. We show that, thanks to tailored interactions (i.e., interactions designed according to a nonconvex alternating direction method of multipliers, or ADMM, scheme), the proposed solution is equivalent to solving the centralized control problem. With some communication exchange, required by the ADMM scheme at given synchronization steps, the safety of the robots is preserved, that is, collisions with neighboring robots are avoided and the robots stay within the bounds of the environment. In this work, we tested the proposed method to coordinate three autonomous vessels at a canal intersection. Nevertheless, the proposed approach is general and can be applied to different applications and robot models.
Original languageEnglish
Title of host publicationProceedings of 2018 European Control Conference (ECC2018)
Place of PublicationPiscataway, NJ, USA
PublisherIEEE
Pages2523-2528
ISBN (Print)978-3-9524-2699-9
DOIs
Publication statusPublished - 2018
Event16th European Control Conference, ECC 2018 - Limassol, Cyprus
Duration: 12 Jun 201815 Jun 2018
http://www.ecc18.eu/

Conference

Conference16th European Control Conference, ECC 2018
Abbreviated titleECC 2018
Country/TerritoryCyprus
CityLimassol
Period12/06/1815/06/18
Internet address

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-care Otherwise 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

  • Autonomous robots
  • Predictive control for nonlinear systems
  • Maritime

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