Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. Robust Trajectory Planning for Autonomous Parafoils under Wind Uncertainty

Robust Trajectory Planning for Autonomous Parafoils under Wind Uncertainty

Thumbnail Image
Download
Name

How_Robust trajectory.pdf

Size

2.24 MB

Format

Adobe PDF

Checksum (MD5)

14f238ca21f7ae15bfe873e1f0eafc40

Author(s)
How, Jonathan P.
•
Luders, Brandon Douglas
•
Sugel, Ian J.
Date Issued
August 2013
Journal
Proceedings of the AIAA Infotech@Aerospace (I@A) Conference
Publisher
American Institute of Aeronautics and Astronautics
Citation
Luders, Brandon D., Ian Sugel, and Jonathan P. How. “Robust Trajectory Planning for Autonomous Parafoils under Wind Uncertainty.” In AIAA Infotech@Aerospace (I@A) Conference. American Institute of Aeronautics and Astronautics, 2013.
Version
Author's final manuscript
Abstract
A key challenge facing modern airborne delivery systems, such as parafoils, is the ability to accurately and consistently deliver supplies into di cult, complex terrain. Robustness is a primary concern, given that environmental wind disturbances are often highly uncertain and time-varying, coupled with under-actuated dynamics and potentially narrow drop zones. This paper presents a new on-line trajectory planning algorithm that enables a large, autonomous parafoil to robustly execute collision avoidance and precision landing on mapped terrain, even with signi cant wind uncertainties. This algorithm is designed to handle arbitrary initial altitudes, approach geometries, and terrain surfaces, and is robust to wind disturbances which may be highly dynamic throughout the terminal approach. Explicit, real-time wind modeling and classi cation is used to anticipate future disturbances, while a novel uncertainty-sampling technique ensures that robustness to possible future variation is e ciently maintained. The designed cost-to-go function enables selection of partial paths which intelligently trade o between current and reachable future states. Simulation results demonstrate that the proposed algorithm reduces the worst-case impact of wind disturbances relative to state-of-the-art approaches.
MIT Department
Massachusetts Institute of Technology. Aerospace Controls Laboratory
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
http://creativecommons.org/licenses/by-nc-sa/3.0/
Persistent DSpace Link
http://hdl.handle.net/1721.1/81472
DOI of Published Version
https://doi.org/10.2514/6.2013-4584
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.