MROS: Runtime Adaptation For Robot Control Architectures

TL;DR

MROS is a model-based framework that enables runtime adaptation of ROS-based robot control architectures, improving mission quality and reusability without requiring major redesigns.

Contribution

It introduces a novel, reusable, and extensible approach for runtime adaptation in robotic systems using domain-specific languages and ontology-based models.

Findings

Improves mission quality in robotic demonstrations

Enhances reusability across different robotic applications

Demonstrates effectiveness in realistic ROS-based scenarios

Abstract

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.