Abstract
Recent studies focused on the achievement of autonomy
by spacecrafts, with the aim of avoiding the intervention
of the ground control. In this sense, the ARPHA software
prototype has been developed for the automatic failure
detection, identification and recovery (FDIR), and is
based on the on-board analysis of a Dynamic Bayesian
Network (DBN) representing the system behaviour conditioned
by the conditions of components and environment.
In this paper, we describe the main functionalities
of ARPHA, and we apply its FDIR capabilities to
the power supply subsystem of an exploring rover, taking
into account four scenarios leading to anomalies or failures.
The DBN model of the system is described. Then,
we test the execution of ARPHA, together with a rover
simulator providing sensor data and plan data. In particular,
we show the results of diagnosis, prognosis and
recovery, returned by ARPHA when the scenarios occur.
| Lingua originale | Inglese |
|---|---|
| Numero di pagine | 8 |
| Stato di pubblicazione | Pubblicato - 1 gen 2012 |
| Evento | ISAIRAS 2012 - International Symposium on Artificial Intelligence, Robotics and Automation in Space - Torino Durata: 1 gen 2012 → … |
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| ???event.eventtypes.event.conference??? | ISAIRAS 2012 - International Symposium on Artificial Intelligence, Robotics and Automation in Space |
|---|---|
| Città | Torino |
| Periodo | 1/01/12 → … |
Keywords
- Dynamic Bayesian Networks
- Fault detection identification and recovery
- Probabilistic Graphical Models