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Model-driven self-adaptation of robotics software using probabilistic approach

  • ENSTA ParisTech
  • Institut VEDECOM

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

A typical feature of robotic architectures are its reactivity and self-adaptivity. In practice, this is achieved by context-dependent dynamic invocation of software components in robotic architectures. In this paper, we specifically address how this self-adaptation capability can be formally defined and modeled in an architecture-independent way. We propose a probabilistic approach that facilitates system design and dynamic runtime adaptation satisfying the quality requirements. We also show how such techniques are incorporated in our model-driven framework: Self Adaptive Framework for Robotic Systems.

Original languageEnglish
Title of host publication2015 European Conference on Mobile Robots, ECMR 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467391634
DOIs
Publication statusPublished - 10 Nov 2015
Externally publishedYes
EventEuropean Conference on Mobile Robots, ECMR 2015 - Lincoln, United Kingdom
Duration: 2 Sept 2015 → 4 Sept 2015

Publication series

Name2015 European Conference on Mobile Robots, ECMR 2015 - Proceedings

Conference

ConferenceEuropean Conference on Mobile Robots, ECMR 2015
Country/TerritoryUnited Kingdom
CityLincoln
Period2/09/15 → 4/09/15

Keywords

  • Adaptation models
  • Analytical models
  • Computational modeling
  • Logic gates
  • Robots
  • Runtime
  • Vehicles

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