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Planning with Diversified Models for Fault-Tolerant Robots

Abstract : Planners are central to the notion of complex autonomous systems. They provide the flexibility that autonomous systems need to be able to operate unattended in an unknown and dynamically-changing environment. However, they are notoriously hard to validate. This paper reports an investigation of how redundant , diversified models can be used as a complement to testing, in order to tolerate residual development faults. A fault-tolerant temporal planner has been designed and implemented using diversity, and its effectiveness demonstrated experimentally through fault injection. The paper describes the implementation of the fault-tolerant planner and discusses the results obtained. The results indicate that diversification provides a noticeable improvement in planning dependability (measured, for instance, by the robustness of the plans it produces) with a negligible performance overhead. However, further improvements in dependability will require implementation of an on-line checking mechanism for assessing plan validity before execution.
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Contributor : Jérémie Guiochet <>
Submitted on : Wednesday, March 23, 2016 - 6:03:29 PM
Last modification on : Thursday, June 10, 2021 - 3:06:22 AM
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  • HAL Id : hal-01292650, version 1


Benjamin Lussier, Matthieu Gallien, Jérémie Guiochet, Félix Ingrand, Marc-Olivier Killijian, et al.. Planning with Diversified Models for Fault-Tolerant Robots. The International Conference on Automated Planning and Scheduling (ICAPS), Sep 2007, Providence, RI, United States. pp.216-223. ⟨hal-01292650⟩



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