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This paper proposes a Priority-driven Accelerator Access Management (PAAM) framework for multi-process robotic applications built on top of the Robot Operating System (ROS) 2 middleware platform. The framework addresses the issue of predictable execution of time- and safety-critical callback chains that require hardware accelerators such as GPUs and TPUs. PAAM provides a standalone ROS executor that acts as an accelerator resource server, arbitrating accelerator access requests from all other callbacks at the application layer. This approach enables coordinated and priority-driven accelerator access management in multi-process robotic systems. The framework design is directly applicable to all types of accelerators and enables granular control over how specific chains access accelerators, making it possible to achieve predictable real-time support for accelerators used by safety-critical callback chains without making changes to underlying accelerator device drivers. The paper shows that PAAM also offers a theoretical analysis that can upper bound the worst-case response time of safety-critical callback chains that necessitate accelerator access. This paper also demonstrates that complex robotic systems with extensive accelerator usage that are integrated with PAAM may achieve up to a 91% reduction in end-to-end response time of their critical callback chains. 

In ROS (Robot Operating System), most applications in time- and safety-critical domain are constructed in the form of callback chains with data dependencies. Due to the shortcomings in its real-time support, ROS does not provide a strong timing guarantee and may lead to disastrous results. Although ROS2 claims to enhance the real-time capability, ensuring predictable end-to-end chain latency still remains a challenging problem. In this paper, we propose a new priority-driven chain-aware scheduler for the ROS2 framework and present end-to-end latency analysis for the proposed scheduler. With our scheduler, callbacks are prioritized based on the given timing requirements of the corresponding chains so that the end-to-end latency of critical chains can be improved with a predictable bound. The proposed scheduling design includes priority assignment and resource allocation considering all ROS2 scheduling-related abstractions, e.g., callbacks, nodes, and executors. To the best of our knowledge, this is the first work to address the inherent limitations of ROS2 in end-to-end latency by proposing a new scheduler design. We have implemented our scheduler in ROS2 running on NVIDIA Xavier NX. We have conducted case studies and schedulability experiments. The results show that the proposed scheduler yields a substantial improvement in end-to-end latency over the default ROS2 scheduler and the latest work in real-world scenarios. 

Intermittently-powered devices have gained much interest in recent years. However, scheduling real-time tasks while supporting data consistency, timekeeping, and schedulability guarantees on these devices still remains a challenge. Many sensing tasks need long indivisible sensor reading operations, but most prior work has limited their focus to the forward progress of computation-only tasks. In this paper, we propose a scheduling framework to execute real-time periodic tasks with atomic sensing operations. Our proposed method keeps track of time progress and ensures the periodic execution of sensing tasks while efficiently utilizing intermittent power sources. We provide schedulability analysis to determine if a taskset is schedulable under a given charging condition. As a proof-of-concept, we design a custom programmable RFID tag device, called R’tag, and demonstrate the effectiveness of our framework in a realistic sensing application. Evaluation results show that the proposed method satisfies the real-time task execution requirements on IPDs in terms of task scheduling, timekeeping, and periodic sensing while significantly outperforming prior work.