A CBF-Adaptive Control Architecture for Visual Navigation for UAV in the Presence of Uncertainties
<|reference_start|>A CBF-Adaptive Control Architecture for Visual Navigation for UAV in the Presence of Uncertainties: 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 is tracked by an adaptive controller 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.<|reference_end|>
@article{sankaranarayanan2024a,
    title={A CBF-Adaptive Control Architecture for Visual Navigation for UAV in the
  Presence of Uncertainties},
    author={Viswa Narayanan Sankaranarayanan, Akshit Saradagi, Sumeet Satpute, and
  George Nikolakopoulos},
    journal={2024 IEEE International Conference on Robotics and Automation
  (ICRA)},
    year={2024},
    doi={10.1109/ICRA57147.2024.10611530},
    archivePrefix={arXiv},
    eprint={2402.10729},
    primaryClass={cs.RO cs.SY eess.SY}
}