Autonomous MAV Landing on a Moving Platform with Estimation of Unknown Turbulent Wind Conditions
Name
AIAA_SciTech_2021___Autonomous_MAV_Landing_on_a_Moving_Platform.pdf
Description
Accepted version
Size
4.38 MB
Format
Adobe PDF
Checksum (MD5)
47fba36842c2b4e83c99970f12e0543b
Author(s)
Paris, Aleix
Tagliabue, Andrea
How, Jonathan P
Date Issued
January 2021
Journal
AIAA Scitech 2021 Forum
Publisher
American Institute of Aeronautics and Astronautics
Citation
Paris, Aleix et al. "Autonomous MAV Landing on a Moving Platform with Estimation of Unknown Turbulent Wind Conditions." AIAA Scitech 2021 Forum, January 2021, virtual event, American Institute of Aeronautics and Astronautics, January 2021. © 2021 American Institute of Aeronautics and Astronautics Inc
Version
Author's final manuscript
Abstract
This paper presents an autonomous landing of a micro aerial vehicle (MAV) on a moving platform immersed in turbulent wind conditions. We estimate the 3D wind vector acting on the vehicle using a model-based and a deep learning-based approach. A disturbance-aware boundary layer sliding controller then uses this estimation to generate a control input that provides trajectory tracking guarantees in the presence of unknown, but bounded disturbances. The approach presented integrates our previous works on control and estimation, and we show its performance in a challenging setting. The experiments show that our methods enable fast landing on a moving platform in turbulent, unknown wind conditions.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.2514/6.2021-0378
