Combining Quality of Service and System Health Metrics in MAPE-K based ROS Systems through Behavior Trees

In recent years, the field of robotics has witnessed a significant shift from operating in structured environments to handling dynamic and unpredictable settings. To tackle these challenges, methodologies from the field of self-adaptive systems enabling these systems to react to unforeseen circumstances during runtime have been applied. The Monitoring-Analysis- Planning-Execution over Knowledge (MAPE-K) feedback loop model is a popular approach, often implemented in a managing subsystem, responsible for monitoring and adapting a managed subsystem. This work explores the implementation of the MAPE- K feedback loop based on Behavior Trees (BTs) within the Robot Operating System 2 (ROS2) framework. By delineating the managed and managing subsystems, our approach enhances the flexibility and adaptability of ROS-based systems, ensuring they not only meet Quality-of-Service (QoS), but also system health metric requirements, namely availability of ROS nodes and communication channels. Our implementation allows for the application of the method to new managed subsystems without needing custom BT nodes as the desired behavior can be configured within a specific rule set. We demonstrate the effectiveness of our method through various experiments on a system showcasing an aerial perception use case. By evaluating different failure cases, we show both an increased perception quality and a higher system availability. Our code is open source