Perception is a critical component of high-integrity applications of robotics and autonomous systems, such as self-driving vehicles. In these applications, failure of perception systems may put human life at risk, and a broad adoption of these technologies requires the development of methodologies to guarantee and monitor safe operation. Despite the paramount importance of perception systems, currently there is no formal approach for system-level monitoring. In this work, we propose a mathematical model for runtime monitoring and fault detection and identification in perception systems. Towards this goal, we draw connections with the literature on diagnosability in multiprocessor systems, and generalize it to account for modules with heterogeneous outputs that interact over time. The resulting temporal diagnostic graphs (i) provide a framework to reason over the consistency of perception outputs -- across modules and over time -- thus enabling fault detection, (ii) allow us to establish formal guarantees on the maximum number of faults that can be uniquely identified in a given perception system, and (iii) enable the design of efficient algorithms for fault identification. We demonstrate our monitoring system, dubbed PerSyS, in realistic simulations using the LGSVL self-driving simulator and the Apollo Auto autonomy software stack, and show that PerSyS is able to detect failures in challenging scenarios (including scenarios that have caused self-driving car accidents in recent years), and is able to correctly identify faults while entailing a minimal computation overhead (< 5 ms on a single-core CPU).
翻译:感知是机器人和自动系统(如自驾驶车辆)高度完整性应用的关键组成部分。在这些应用中,感知系统的失败可能危及人的生命,而广泛采用这些技术需要制定保障和监测安全运作的方法。尽管感知系统至关重要,但目前没有系统一级监测的正式方法。在这项工作中,我们提出一个运行时间监测、发现和辨别系统认知系统错误的数学模型。为实现这一目标,我们与多处理器系统中可诊断性文献进行连接,并概括它,以说明具有不同产出的模块在时间上发生相互作用。 由此产生的时间诊断图(一) 提供了一个框架,说明认识产出的一致性 -- -- 跨模块和时间 -- -- 从而能够发现错误;(二) 使我们能够对在特定感知系统中可以独特识别的最大误差数建立正式的保证,以及(三) 能够设计高效的对错觉识别误差的算法。 我们在现实的模拟中展示了我们的监测系统、杜伯·佩斯(dubed Per-S),在使用现实的模型中,在AMS-V-V-Aliximal自动测试中,一个具有挑战性的自动测算的自动测算系统。