NDLI: Computationally adaptive multi-objective trajectory optimization for UAS with variable planning deadlines

Content Provider	IEEE Xplore Digital Library
Author	Narayan, P. Campbell, D. Walker, R.
Copyright Year	2009
Description	Author affiliation: Queensland University of Technology, 2 George Street, Brisbane, Australia (Narayan, P.; Campbell, D.; Walker, R.)
Abstract	This paper presents a new approach which allows for the computation and optimization of feasible 3D flight trajectories within real time planning deadlines, for Unmanned Aerial Systems (UAS) operating in environments with obstacles present. Sets of candidate flight trajectories have been generated through the application of maneuver automaton theory, where smooth trajectories are formed via the concatenation of predefined trim and maneuver primitives; generated using aircraft dynamic models. During typical UAS operations, multiple objectives may exist, therefore the use of multi-objective optimization can potentially allow for convergence to a solution which better reflects overall mission requirements. Multiple objective optimization of trajectories has been implemented through weighted sum aggregation. However, real-time planning constraints may be imposed on the multi-objective optimization process due to the existence of obstacles in the immediate path. Thus, a novel Computationally Adaptive Trajectory Decision (CATD) optimization system has been developed and implemented in simulation to dynamically manage, calculate and schedule system execution parameters to ensure that the trajectory solution search can generate a feasible solution, if one exists, within a given length of time. The inclusion of the CATD potentially increases overall mission efficiency and may allow for the implementation of the system on different UAS platforms with varying onboard computational capabilities. This approach has been demonstrated in this paper through simulation using a fixed wing UAS operating in low altitude environments with obstacles present.
Starting Page	1
Ending Page	8
File Size	766266
Page Count	8
File Format	PDF
ISBN	9781424426218
ISSN	1095323X
DOI	10.1109/AERO.2009.4839607
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Trajectory Computational modeling Real time systems Automata Aircraft Path planning Process planning Constraint optimization Processor scheduling Dynamic scheduling
Content Type	Text
Resource Type	Article
Subject	Aerospace Engineering Space and Planetary Science

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