RRA: Models and tools for robotics run-time adaptation
| Autor: | Luca Gherardi, Nico Hochgeschwender |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Context model
Resource-oriented architecture Computer science business.industry Database-centric architecture Software Architecture tradeoff analysis method Applications architecture Systems architecture Artificial intelligence Reference architecture Software system Software architecture Space-based architecture business Software engineering Software architecture description |
| Zdroj: | IROS |
| DOI: | 10.1109/iros.2015.7353608 |
| Popis: | Robotics applications are characterized by a huge amount of variability. Their design requires the developers to choose between several variants, which relate to both functionalities and hardware. Some of these choices can be taken at deployment-time, however others should be taken at run-time, when more information about the context is known. To make this possible, a software system needs to be able to reason about its current state and to adapt its architecture to provide the configuration that best suites the context. This paper presents a model-based approach for run-time adaptation of robotic systems. It defines a set of orthogonal models that represent the system architecture, its variability, and the state of the context. Additionally it introduces a set of algorithms that reason about the knowledge represented in our models to resolve the run-time variability and to adapt the system architecture. The paper discusses and evaluates the approach by means of two case studies. |
| Databáze: | OpenAIRE |
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