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Efficient Power-Aware Resource Constrained Scheduling and Execution for Planetary Rovers

Contributo in Atti di convegno
Data di Pubblicazione:
2015
Abstract:
This paper presents and evaluates an integrated power-aware, model-based autonomous control architecture for managing the execution of rover actions in the context of planetary mission exploration. The proposed solution is embedded within an application scenario of reference which consists on a rover-based mission concept aimed at collecting Mars samples that may be returned to Earth at a later date for further investigation. This study elaborates on the exploitation of advanced decision-making capabilities within a flexible execution process targeted at generating and safely executing scheduling solutions representing mission plans, seamlessly supporting online plan optimization and dynamic management of new incoming activities. In this work, an experimental analysis on the performance of the control architecture's capabilities is presented, throughout two representative cases of study running upon an integrated test-bed platform built on top of the 3DROV ESA planetary rover simulator.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
artificial intelligence; data mining and knowledge discovery; mathematical logic and formal languages; computation by abstract devices; user interfaces and human computer interaction; pattern recognition
Elenco autori:
Oddi, Angelo; Rasconi, Riccardo; Cesta, Amedeo
Autori di Ateneo:
CESTA AMEDEO
ODDI ANGELO
RASCONI RICCARDO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/300147
Titolo del libro:
AI*IA 2015 Advances in Artificial Intelligence
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URL

http://dx.doi.org/10.1007/978-3-319-24309-2_29
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