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Kinodynamic Motion Planning via Funnel Control for Underactuated Unmanned Surface Vehicles
KTH Royal Inst Technol, Div Decis & Control Syst, S-11428 Stockholm, Sweden..ORCID iD: 0000-0002-9706-8073
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Signals and Systems.ORCID iD: 0000-0002-4289-2866
KTH Royal Inst Technol, Div Decis & Control Syst, S-11428 Stockholm, Sweden..
KTH Royal Inst Technol, Div Decis & Control Syst, S-11428 Stockholm, Sweden..
2024 (English)In: IEEE Transactions on Control Systems Technology, ISSN 1063-6536, E-ISSN 1558-0865, Vol. 32, no 6, p. 2114-2125Article in journal (Refereed) Published
Abstract [en]

We develop an algorithm to control an underactuated unmanned surface vehicle (USV) using kinodynamic motion planning with funnel control (KDF). KDF has two key components: motion planning used to generate trajectories with respect to kinodynamic constraints, and funnel control, also referred to as prescribed performance control (PPC), which enables trajectory tracking in the presence of uncertain dynamics and disturbances. We extend PPC to address the challenges posed by underactuation and control input saturation present on the USV. The proposed scheme guarantees stability under user-defined prescribed performance functions where model parameters and exogenous disturbances are unknown. Furthermore, we present an optimization problem to obtain smooth, collision-free trajectories while respecting kinodynamic constraints. We deploy the algorithm on a USV and verify its efficiency in real-world open-water experiments.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2024. Vol. 32, no 6, p. 2114-2125
Keywords [en]
Autonomous systems, motion planning, nonlinear control systems, trajectory optimization
National Category
Control Engineering Computer Sciences Robotics and automation
Identifiers
URN: urn:nbn:se:uu:diva-548048DOI: 10.1109/TCST.2024.3396027ISI: 001218626900001Scopus ID: 2-s2.0-85192732380OAI: oai:DiVA.org:uu-548048DiVA, id: diva2:1929843
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)Swedish Research CouncilKnut and Alice Wallenberg FoundationAvailable from: 2025-01-21 Created: 2025-01-21 Last updated: 2025-01-21Bibliographically approved

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Verginis, Christos K.

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