Non-functional properties are an essential part of any software solution. There is a lot of literature on what non-functional properties are but, unfortunately, there is also a lot of disagreement and different points of view on how to deal with them. Non-functional properties, such as safety or dependability, become particularly relevant in the context of robotics. In the EU H2020 RobMoSys Project, non-functional properties are treated as first-class citizens and considered key added-value services. In this vein, the RoQME Integrated Technical Project, funded by RobMoSys, aims at contributing a model-driven tool-chain for dealing with system-level non-functional properties, enabling the specification of global robot Quality of Service (QoS) metrics. The estimation of these metrics at runtime, in terms of the contextual information available, can then be used for different purposes, such as robot behavior adaptation or benchmarking.
Autores: Cristina Vicente-Chicote / Javier Berrocal / José Manuel García-Alonso / Juan Hernández / Antonio Bandera / Jesús Martínez / Adrián Romero-Garcés / Roberto Font / Juan Francisco Inglés-Romero /
Palabras Clave: MDE - Non-functional Properties - QoS metrics - Service Robotics
Este trabajo presenta los resultados obtenidos durante la ejecución del Proyecto RoQME en relación con: (1) el modelado de métricas asociadas a propiedades no funcionales en sistemas robóticos (p. ej., rendimiento, seguridad, grado de interacción/aceptación por parte de los usuarios, etc.); y (2) la generación, a partir de los modelos anteriores, de la infraestructura necesaria para estimar dichas métricas en tiempo de ejecución. Las métricas estimadas pueden ser de utilidad, por ejemplo, para adaptar el comportamiento o la arquitectura del robot, o como fuente de datos para realizar algún tipo de benchmarking.
Autores: Cristina Vicente-Chicote / Daniel García-Pérez / Pablo García-Ojeda / Juan F. Inglés-Romero / Juan Adrian Romero-Garcés / Jesús Martínez /
Palabras Clave: MDE - métricas - Propiedades no funcionales - Robótica - RoQME
Dealing with variability in open-ended environments requires robots to adapt themselves according to the perceived situation in order to achieve the required quality of service (defined in terms of safety, performance or energy consumption, among other criteria). In this sense, context awareness and runtime self-adaptation allows moving autonomous robot navigation one step forward. The ambition of the MIRoN Project was to provide a complete framework enabling designers to endow robots with the ability of self-adapting their course of action at runtime, according to the external and internal context information available. Our proposal relies on the systematic use of models for dynamically reconfiguring the robot behavior, defined in terms of Behavior Trees, according to the runtime prediction and estimation of quality of service metrics based on system-level non-functional properties.
Autores: Juan F. Ingles-Romero / Renan Salles de Freitas / Adrián Romero-Garces / Antonio Bandera / Jesus Martinez / José Ramón Lozano-Pinilla / Daniel Garcia-Pérez / Cristina Vicente-Chicote /
Palabras Clave: context-awareness - EU H2020 R&D Projects - Robotics - Self-Adaptation
Comprehensive Geriatric Assessment (CGA) is an integrated clinical process to evaluate frail elderly people in order to provide them with customized therapy plans. The whole process includes the completion of standardized questionnaires or specific movements, which are performed by the patient and do not necessarily require the presence of a medical expert. With the aim to automate CGA tests in as much as possible, we have designed and developed CLARC: a mobile robot aimed at helping physicians to capture and manage data during the CGA procedures, mainly by autonomously conducting a set of predefined tests. The design of CLARC has required dealing with both functional (robot’s skills and tasks) and non-functional aspects (e.g. performance, safety, or user satisfaction, among others). This paper describes a novel model-based approach aimed at helping designers (1) to specify the contextual information available to the robot; the Non-Functional Properties (NFP considered relevant for a given application; and how (and to what extent) changes in the context may affect these properties; and, from these models (2) to generate the runtime infrastructure allowing the robot to monitor its execution context and estimate high-level QoS metrics to know how well it is performing in terms of the selected NFPs.
Autores: Adrián Romero-Garcés / Jesús Martínez / Juan F. Inglés Romero / Cristina Vicente-Chicote / Rebeca Marfil / Antonio J. Bandera /
Palabras Clave: Assistive robotics - Model-Driven Engineering - Non-functional Properties - QoS metrics