Online learning of autonomous helicopter control
| Contribuinte(s) |
Friedrich, W. |
|---|---|
| Data(s) |
01/11/2002
|
| Resumo |
This paper details the development of an online adaptive control system, designed to learn from the actions of an instructing pilot. Three learning architectures, single layer neural networks (SLNN), multi-layer neural networks (MLNN), and fuzzy associative memories (FAM) are considerd. Each method has been tested in simulation. While the SLNN and MLNN provided adequate control under some simulation conditions, the addition of pilot noise and pilot variation during simulation training caused these methods to fail. |
| Formato |
application/pdf |
| Identificador | |
| Publicador |
Australian Robotics Automation Association |
| Relação |
http://eprints.qut.edu.au/83378/1/__staffhome.qut.edu.au_staffgroupm%24_meaton_Desktop_Online.Learning.of.Autonomous.Helicopter.Control.pdf http://www.araa.asn.au/acra/acra2002/Papers/Buskey-Roberts-Wyeth.pdf Buskey, Gregg, Roberts, Jonathan M., & Wyeth, Gordon (2002) Online learning of autonomous helicopter control. In Friedrich, W. (Ed.) Proceedings of the 2002 Australasian Conference on Robotics and Automation (ACRA 2002), Australian Robotics Automation Association, Auckland, New Zealand, pp. 21-27. |
| Direitos |
Copyright 2002 Australian Robotics Automation Association |
| Fonte |
School of Electrical Engineering & Computer Science; Science & Engineering Faculty |
| Palavras-Chave | #Adaptive control system #SLNN #MLNN #FAM |
| Tipo |
Conference Paper |
