9,710 research outputs found
Engineering context-aware systems and applications:A survey
Context-awareness is an essential component of systems developed in areas like Intelligent Environments, Pervasive & Ubiquitous Computing and Ambient Intelligence. In these emerging fields, there is a need for computerized systems to have a higher understanding of the situations in which to provide services or functionalities, to adapt accordingly. The literature shows that researchers modify existing engineering methods in order to better fit the needs of context-aware computing. These efforts are typically disconnected from each other and generally focus on solving specific development issues. We encourage the creation of a more holistic and unified engineering process that is tailored for the demands of these systems. For this purpose, we study the state-of-the-art in the development of context-aware systems, focusing on: (A) Methodologies for developing context-aware systems, analyzing the reasons behind their lack of adoption and features that the community wish they can use; (B) Context-aware system engineering challenges and techniques applied during the most common development stages; (C) Context-aware systems conceptualization
Applying Software Product Lines to Build Autonomic Pervasive Systems
In this Master Thesis, we have proposed a model-driven Software Product Line (SPL) for developing autonomic pervasive systems. The work focusses on reusing the Variability knowledge from the SPL design to the SPL products. This Variability knowledge enables SPL products to deal with adaptation scenarios (evolution and involution) in an autonomic way.Cetina Englada, C. (2008). Applying Software Product Lines to Build Autonomic Pervasive Systems. http://hdl.handle.net/10251/12447Archivo delegad
MROS: Runtime Adaptation For Robot Control Architectures
Known attempts to build autonomous robots rely on complex control
architectures, often implemented with the Robot Operating System platform
(ROS). Runtime adaptation is needed in these systems, to cope with component
failures and with contingencies arising from dynamic environments-otherwise,
these affect the reliability and quality of the mission execution. Existing
proposals on how to build self-adaptive systems in robotics usually require a
major re-design of the control architecture and rely on complex tools
unfamiliar to the robotics community. Moreover, they are hard to reuse across
applications.
This paper presents MROS: a model-based framework for run-time adaptation of
robot control architectures based on ROS. MROS uses a combination of
domain-specific languages to model architectural variants and captures mission
quality concerns, and an ontology-based implementation of the MAPE-K and
meta-control visions for run-time adaptation. The experiment results obtained
applying MROS in two realistic ROS-based robotic demonstrators show the
benefits of our approach in terms of the quality of the mission execution, and
MROS' extensibility and re-usability across robotic applications
NASA space station automation: AI-based technology review
Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures
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