Fast Trajectory Optimization using Sequential Convex Programming with No-Fly Zone Constraints

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This paper proposes a new trajectory optimization method for Unmanned Aerial Vehicle (UAV). The proposed L1-Penalized Sequential Convex Programming (LPSCP) method improves the initial infeasibility of the standard sequential convex programming. LPSCP method converges within 0.2 seconds which is more than one-tenth of the pseudospectral (PS) method. Therefore, LPSCP has the potential to enable UAV's real-time autonomous air mission if implemented on-board. The UAV trajectory optimization problem is defined at the beginning of the paper and a convexification process is performed when there are several no-fly zones along the trajectory. Then the LPSCP method iteratively solves locally approximated subproblems in conic forms. Simulation results illustrate the proposed method satisfies the required constraints and has a computation time advantage over the conventional PS method. Copyright (C) 2019. The Authors. Published by Elsevier Ltd. All rights reserved.
Publisher
ELSEVIER
Issue Date
2019-08
Language
English
Citation

21st International-Federation-of-Automatic-Control (IFAC) Symposium on Automatic Control in Aerospace (ACA), pp.298 - 303

ISSN
2405-8963
DOI
10.1016/j.ifacol.2019.11.259
URI
http://hdl.handle.net/10203/274959
Appears in Collection
AE-Conference Papers(학술회의논문)
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