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A CBF-Adaptive Control Architecture for Visual Navigation for UAV in the Presence of Uncertainties
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-1883-7912
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0003-3794-0306
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0003-1437-1809
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0003-0126-1897
2024 (English)In: 2024 IEEE International Conference on Robotics and Automation (ICRA), IEEE, 2024, p. 13659-13665Conference paper, Published paper (Refereed)
Abstract [en]

In this article, we propose a control solution for the safe transfer of a quadrotor UAV between two surface robots positioning itself only using the visual features on the surface robots, which enforces safety constraints for precise landing and visual locking, in the presence of modeling uncertainties and external disturbances. The controller handles the ascending and descending phases of the navigation using a visual locking control barrier function (VCBF) and a parametrizable switching descending CBF (DCBF) respectively, eliminating the need for an external planner. The control scheme has a backstepping approach for the position controller with the CBF filter acting on the position kinematics to produce a filtered virtual velocity control input, which an adaptive controller tracks to overcome modeling uncertainties and external disturbances. The experimental validation is carried out with a UAV that navigates from the base to the target using an RGB camera.

Place, publisher, year, edition, pages
IEEE, 2024. p. 13659-13665
National Category
Control Engineering Robotics and automation
Research subject
Robotics and Artificial Intelligence
Identifiers
URN: urn:nbn:se:ltu:diva-109775DOI: 10.1109/ICRA57147.2024.10611530Scopus ID: 2-s2.0-85202433253OAI: oai:DiVA.org:ltu-109775DiVA, id: diva2:1895949
Conference
2024 IEEE International Conference on Robotics and Automation (ICRA), Yokohama, Japan, May 13-17, 2024
Note

Funder: Horizon 2020 (953454);

ISBN for host publication: 979-8-3503-8457-4;

Available from: 2024-09-09 Created: 2024-09-09 Last updated: 2025-02-05Bibliographically approved

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Sankaranarayanan, Viswa NarayananSaradagi, AkshitSatpute, SumeetNikolakopoulos, George

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