Since future air combat missions will involve both manned and unmanned aircraft, the primary motivation for this
research is to enable unmanned aircraft with intelligent maneuvering capabilities. During air combat maneuvering, pilots
use their knowledge and experience of maneuvering strategies and tactics to determine the best course of action. As a
result, we try to capture these aspects using an artificial immune system approach. The biological immune system
protects the body against intruders by recognizing and destroying harmful cells or molecules. It can be thought of as a
robust adaptive system that is capable of dealing with an enormous variety of disturbances and uncertainties. However,
another critical aspect of the immune system is that it can remember how previous encounters were successfully
defeated. As a result, it can respond faster to similar encounters in the future. This paper describes how an artificial
immune system is used to select and construct air combat maneuvers. These maneuvers are composed of autopilot mode
and target commands, which represent the low-level building blocks of the parameterized system. The resulting
command sequences are sent to a tactical autopilot system, which has been enhanced with additional modes and an
aggressiveness factor for enabling high performance maneuvers. Just as vaccinations train the biological immune system
how to combat intruders, training sets are used to teach the maneuvering system how to respond to different enemy
aircraft situations. Simulation results are presented, which demonstrate the potential of using immunized maneuver
selection for the purposes of air combat maneuvering.
The National Aeronautics and Space Administration (NASA), Aeronautics Research Mission Directorate, is developing Intelligent Mission Management (IMM) technology for Uninhabited Aerial Vehicles (UAV’s) under the Vehicle Systems Program’s Autonomous Robust Avionics Project. The objective of the project is to develop air vehicle and associated ground element technology to enhance mission success by increasing mission return and reducing mission risk. Unanticipated science targets, uncertain conditions and changing mission requirements can all influence a flight plan and may require human intervention during the flight; however, time delays and communications bandwidth limit opportunities for operator intervention. To meet these challenges, we will develop UAV-specific technologies enabling goal-directed autonomy, i.e. the ability to redirect the flight in response to current conditions and the current goals of the flight. Our approach divides goal-directed autonomy into two components, an on-board Intelligent Agent Architecture (IAA) and a ground based Collaborative Decision Environment (CDE). These technologies cut across all aspects of a UAV system, including the payload, inner- and outer-loop onboard control, and the operator’s ground station.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.