RoboSpike: Fully Utilizing the Heterogeneous System With Subcallback Scheduling in ROS 2

Abstract

The advancement in artificial intelligence (AI) has greatly propelled the development of robotics, requiring the adoption of heterogeneous computing architectures with multicore CPUs, GPUs, and accelerators to meet the growing computational needs of edge computing. Such heterogeneity, coupled with the inherently IO-intensive nature of robotic applications, poses substantial challenges for task scheduling and resource management. These challenges are particularly acute for systems striving to maximize computational resource utilization, which cannot be effectively addressed through callback-level scheduling. To overcome these obstacles, we developed RoboSpike, a systematic solution built on the Robot Operating System 2 (ROS 2). We first implemented a subcallback scheduling mechanism utilizing coroutines to utilize the blocked CPUs which wait for I/O operations. Building on this mechanism, we extended the design to incorporate the coprocessor and introduced an auto-tuning algorithm to adapt to system performance variations. Finally, we performed the response time analysis to ensure that the RoboSpike is predictable in time. The evaluation results demonstrate that RoboSpike achieves substantial improvements, increasing throughput by 1.65–2.25 times in real-world scenarios. RoboSpike enhances the scheduling capabilities of ROS 2 by refining the granularity from the callback level, thus opening up new opportunities for performance improvement in robotic systems, especially in resource-limited scenarios with complex workloads.