Hybrid Scheduling Executor and Chain-Aware Thread Mapping Strategy for ROS 2

The second-generation Robot Operating System, ROS 2, is a middleware framework for developing robot applications. As robot systems become increasingly complex, the demand for simultaneously handling mixed tasks (critical and ordinary tasks) has markedly risen; critical tasks are characterized by real-time constraints, while ordinary tasks emphasize fairness. However, the existing researches on ROS 2 executors are limited to employing either a real-time scheduling approach or a fair scheduling approach, failing to accommodate different scheduling strategies for varying task types. And ROS 2 executors cannot isolate critical tasks from the interference of ordinary tasks which compromises the real-time performance of systems. In this paper, we propose a hybrid scheduling executor (HSE) for ROS 2, which mainly incorporates two schedulers—fair and real-time, and two thread types—shared and exclusive. The fair scheduler is responsible for managing ordinary tasks through shared threads, while the real-time scheduler handles critical tasks using both exclusive and shared threads. Additionally, we analyze the scheduling behavior of the HSE and the timing characteristics of task chains to design a chain-aware thread mapping strategy (CATMS). Given a fixed number of CPUs, CATMS aims to map threads to CPUs to optimizes performance while meeting real-time constraints. To the best of our knowledge, this is the first work to address the challenge of integrating critical and ordinary tasks in robotic systems by enhancing the architecture of ROS 2 executors. Through experimental evaluation, we assess the performance of HSE and CATMS. The results show that the HSE achieves real-time performance comparable to the existing executors, while maintaining fairness comparable to the default executor. Furthermore, HSE enhances the real-time performance by including exclusive threads, and CATMS can maximize performance while meeting real-time constraints when operating with a specified number of CPUs.