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Model predictive control for autonomous ship landing in a search and rescue scenario
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0002-1124-5009
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0002-1927-1690
2019 (English)In: Model predictive control for autonomous ship landing in a search and rescue scenario, San Diego, 2019, p. 1169-Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a Model Predictive Control approach for autonomous landing of a quadcopter on the deck of a moving boat. The research is motivated by a large-scale demonstrator arena equipped with autonomous boats and drones that should collaborate to perform various tasks related to search and rescue missions. The landing maneuver is executed in a cooperative manner where both the boat and the drone take actions to reach their common objective. The maneuver is designed to be feasible under a range of conditions, including scenarios where the boat is moving across the water or when it is subjected to disturbances such as waves and winds. During the landing, the vehicles must also consider various safety constraints for landing safely and efficiently. The algorithms are implemented both in hardware-in-the-loop simulations, where we demonstrate some of the different scenarios that the algorithm is expected to handle, as well as on a real boat-drone system, on which initial tests have been carried out.

Place, publisher, year, edition, pages
San Diego, 2019. p. 1169-
Keywords [en]
MPC, model predictive control, cooperative control, UAV, USV, autonomous landing, cooperative landing
National Category
Control Engineering
Research subject
Electrical Engineering; Aerospace Engineering
Identifiers
URN: urn:nbn:se:kth:diva-267220DOI: 10.2514/6.2019-1169Scopus ID: 2-s2.0-85068462709OAI: oai:DiVA.org:kth-267220DiVA, id: diva2:1391443
Conference
AIAA Scitech 2019 Forum
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)
Note

QC 20200205

Available from: 2020-02-04 Created: 2020-02-04 Last updated: 2020-02-05Bibliographically approved

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Persson, LinneaWahlberg, Bo

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