Planetary rovers provide a considerable challenge for robotic systems in that they must operate for long periods autonomously, or with relatively little intervention. To achieve this, they need to have on-board fault detection and diagnosis capabilities in order to determine the actual state of the vehicle, and decide what actions are safe to perform. Traditional model-based diagnosis techniques are not suitable for rovers due to the tight coupling between the vehicle's performance and its environment. Hybrid diagnosis using particle filters is presented as an alternative, and its strengths and weakeners are examined. We also present some extensions to particle filters that are designed to make them more suitable for use in diagnosis problems.
Particle Filters for Real-Time Fault Detection in Planetary Rovers
ESA Workshop on On-Board Autonomy
2001-01-01
Preprint
No indication
English
Cognitive Maps for Planetary Rovers
British Library Online Contents | 2001
|Toward remotely controlled planetary rovers.
NTRS | 1972
|Inflatable rovers for planetary applications
SPIE | 1999
|Active localization for planetary rovers
IEEE | 2016
|