NDLI: Automating Human Thought Processes for a UAV Forced Landing

Content Provider	Springer Nature Link
Author	Eng, Pillar Mejias, Luis Liu, Xi Walker, Rodney
Copyright Year	2009
Abstract	This paper describes the current status of a program to develop an automated forced landing system for a fixed-wing Unmanned Aerial Vehicle (UAV). This automated system seeks to emulate human pilot thought processes when planning for and conducting an engine-off emergency landing. Firstly, a path planning algorithm that extends Dubins curves to 3D space is presented. This planning element is then combined with a nonlinear guidance and control logic, and simulated test results demonstrate the robustness of this approach to strong winds during a glided descent. The average path deviation errors incurred are comparable to or even better than that of manned, powered aircraft. Secondly, a study into suitable multi-criteria decision making approaches and the problems that confront the decision-maker is presented. From this study, it is believed that decision processes that utilize human expert knowledge and fuzzy logic reasoning are most suited to the problem at hand, and further investigations will be conducted to identify the particular technique/s to be implemented in simulations and field tests. The automated UAV forced landing approach presented in this paper is promising, and will allow the progression of this technology from the development and simulation stages through to a prototype system.
Starting Page	329
Ending Page	349
Page Count	21
File Format	PDF
ISSN	09210296
Journal	Journal of Intelligent & Robotic Systems
Volume Number	57
Issue Number	1-4
e-ISSN	15730409
Language	English
Publisher	Springer Netherlands
Publisher Date	2009-11-12
Publisher Place	Dordrecht
Access Restriction	Subscribed
Subject Keyword	UAV Forced landing Path planning Control Multi-criteria decision making Mechanical Engineering Artificial Intelligence (incl. Robotics) Electrical Engineering Control , Robotics, Mechatronics
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Artificial Intelligence Control and Systems Engineering Mechanical Engineering Electrical and Electronic Engineering Software

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