A Safety-Performance Metric Enabling Computational Awareness in Autonomous Robots
A Safety-Performance Metric Enabling Computational Awareness in Autonomous Robots
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DOI：
10.1109/lra.2023.3300251
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发表时间：
2023-09
影响因子：
5.2
通讯作者：
Ashrarul H. Sifat;Xuanliang Deng;Burhanuddin Bharmal;Sen Wang;Shao-Yu Huang;Jiabin Huang;Chang-Rae Jung;Haibo Zeng;Ryan K. Williams
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文献类型：
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作者：
Ashrarul H. Sifat;Xuanliang Deng;Burhanuddin Bharmal;Sen Wang;Shao-Yu Huang;Jiabin Huang;Chang-Rae Jung;Haibo Zeng;Ryan K. Williams
这封信迈出了分析自主机器人安全和性能关键计算任务的第一步。我们的贡献是一个安全性能（SP）指标，确保安全第一，然后奖励实时计算任务的性能提高，建立在“名义上的安全”的概念，它定义了及时的计算是至关重要的安全。为了充分利用异构处理单元的计算能力（例如，为了描述机器人应用的不确定性及其所需的计算量，采用了一种称为随机异构并行有向无环图（SHP-DAG）的计算任务图模型。与现有的任务模型相比，SHP-DAG避免了确定性最坏情况执行时间（WCET）的悲观主义，而是通过概率分布来建模任务的执行时间。我们的SP指标定义在这个任务模型上，这使我们能够将Linux内核的FIFO和CFS处理器应用于复杂的机器人计算任务，并将SP指标与基线指标、平均和最坏情况的完工时间进行比较。在NVIDIA Jetson AGX Xavier硬件上进行的大量实验结果表明，所提出的SP指标适用于以平衡机器人系统安全性和性能的方式管理计算任务。
This letter takes a first step towards the analysis of safety and performance critical computational tasks for autonomous robots. Our contribution is a safety-performance (SP) metric that ensures safety first and then rewards improved performance of real-time computational tasks, building on the notion of “nominal safety” which defines timely computation as critical to safety. To fully utilize the computing capacity of heterogeneous processing units (e.g., CPU + GPU), a computational task graph model called the Stochastic Heterogeneous Parallel Directed Acyclic Graph (SHP-DAG) is adopted to capture the uncertain nature of robotic applications and their required computation. Compared to state-of-the-art task models, SHP-DAG avoids the pessimism of deterministic worst-case execution time (WCET), instead modeling the execution times of tasks by probability distributions. Our SP metric is defined upon this task model, which allows us to apply the FIFO and CFS schedulers of the Linux kernel on complex robotic computational tasks and compare the SP metric with baseline metrics, average and worst-case makespan. Extensive experimental results on NVIDIA Jetson AGX Xavier hardware demonstrate that the proposed SP metric is appropriate for managing computational tasks in a manner that balances safety and performance in robotic systems.