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RESEARCH |
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TOWARDS THE NEXT GENERATION OF AUTOPILOTS |
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We have developed the Intelligent Autopilot System (IAS) which not only can
perform full flight cycles safely and autonomously from one location to another, but also
handle flight uncertainties such as extreme weather conditions beyond the current
limits and abilities, and emergency situations. The Intelligent Autopilot System (IAS) learns
how to perform piloting tasks and the required skills from human teachers
by applying the Learning by Imitation concept with
Artificial Neural Networks, and using an approach that requires few examples
and small training datasets, which speeds up development ,enhances performance,
eliminates the black-box issue, and makes comprehensive V&V possible.
The IAS can either be applied as an advanced digital co-pilot which a human captain
can completely rely on, or a fully autonomous pilot that can fly on its own. The IAS can
increase safety by tackling issues such as the low capabilities of modern autopilots,
stress, information overload, emergencies, and sometimes the lack of sufficient
and up to date training. The IAS can also lower costs associated with the need
for more than one pilot in the cockpit, or ground control facilities and staff
in the case of Unmanned Aerial Systems. |
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RESEARCH PAPERS |
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Baomar, H., Bentley, P. J. Autonomous Flight Cycles and Extreme Landings
Airliners Beyond the Current Limits and Capabilities Using Artificial
Neural Networks. Appl Intell (2021).
30th Anniversary Special Issue |
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H. Baomar and P. J. Bentley, "An Intelligent Autopilot System that learns Piloting Skills
from Human Pilots by Imitation", 2016 International Conference on Unmanned Aircraft
Systems (ICUAS), Arlington, VA, USA, 2016, pp. 1023-1031. |
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H. Baomar and P. J. Bentley, "An Intelligent Autopilot System that Learns Flight Emergency
Procedures by Imitating Human Pilots", 2016 IEEE Symposium Series on IEEE
Symposium Series on Computational Intelligence (SSCI), Athens, 2016, pp. 1-9. |
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H. Baomar and P. J. Bentley, "Autonomous Navigation and Landing of Airliners Using
Artificial Neural Networks and Learning by Imitation", 2017 IEEE Symposium Series on
Computational Intelligence (SSCI), Hawaii, USA, 2017. |
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H. Baomar and P. J. Bentley, "Autonomous Landing and Go-around of Airliners
Under Severe Weather Conditions Using Artificial Neural Networks", The 2017
International Workshop on Research, Education and Development on Unmanned
Aerial Systems (RED-UAS), Linköping, Sweden, 2017. |
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| PDF link |