Title :
Fault-diagnosis of subsea robots using neuro-symbolic hybrid systems
Author :
Deuker, B. ; Perrier, M. ; Amy, B.
Author_Institution :
IFREMER, Subsea Robotics & Artificial Intelligence Lab., La Seyne-sur-Mer, France
fDate :
28 Sep-1 Oct 1998
Abstract :
We describe a diagnosis phase, part of a study currently performed on subsea robots health monitoring. The overall objective of this study is to allow a subsea robot with sub-system failure to keep executing its mission with a certain level of performance. The current development of the diagnosis phase is based on the use of neuro-symbolic hybrid systems. With this solution, the system is able to learn when it meets unforeseen failures
Keywords :
computerised monitoring; fault diagnosis; fault tolerance; mobile robots; neurocontrollers; underwater vehicles; fault tolerance; fault-diagnosis; health monitoring; hybrid neural symbolic systems; model based diagnosis; subsea robots; underwater vehicles; Actuators; Artificial intelligence; Condition monitoring; Failure analysis; Intelligent robots; Laboratories; Phase detection; Robot sensing systems; Testing; Underwater vehicles;
Conference_Titel :
OCEANS '98 Conference Proceedings
Conference_Location :
Nice
Print_ISBN :
0-7803-5045-6
DOI :
10.1109/OCEANS.1998.724354
