ROSRV: Runtime Verification for Robots

Huang, Jeff; Erdogan, Cansu; Zhang, Yi; Moore, B.; Luo, Qingzhou; Sundaresan, Aravind; Roşu, Grigore

doi:10.1007/978-3-319-11164-3_20

Cited by 85 publications

(62 citation statements)

References 4 publications

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“…Temporal Logic 0 [29], [36], [57], [55], [61], [62], [70], [71], [83], [95], [97], [98], [51], [99], [104], [108], [110], [111], [115], [116], [123], [129], [138], [141], [176], [174], [175] 27…”

Section: Logics 6 32mentioning

confidence: 99%

“…Some systems specifications are checked for deadlock or reachability, for example [49]; whereas some are just used for specification, such as [177]. Conversely, some of the studies only specify properties and monitor a running system [95,117], or describe a framework for dealing with property specification [180]. Also, the ontologies found in our literature search are all used to specify systems.…”

Section: Summary Of Formalisms For Robotic Systemsmentioning

confidence: 99%

“…Theorem Proving [125], [89], [113] 3 Runtime Monitoring [95], [66], [117] 3 Integrated Formal Methods [51], [43], [6], [29], [89], [81], [97], [117] 8 Formal Software Frameworks /Architectures [66], [141], [24], [179], [20], [18], [25], [138], [139], [178] 10 Table 4: Summary of the approaches to formal verification found using the methodology described in §1.1. Note: some of the surveyed papers use more than one approach.…”

Section: References Totalmentioning

confidence: 99%

“…It has received attention in the literature on runtime verification, which brings together model-checking and stream-processing technologies [148]. Examples include [66,97,95], and the International Conference on Runtime Verification has been running since 2006.…”

Section: Runtime Monitoringmentioning

confidence: 99%

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Formal Specification and Verification of Autonomous Robotic Systems

et al. 2019

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Autonomous robotic systems are complex, hybrid, and often safety-critical; this makes their formal specification and verification uniquely challenging. Though commonly used, testing and simulation alone are insufficient to ensure the correctness of, or provide sufficient evidence for the certification of, autonomous robotics. Formal methods for autonomous robotics has received some attention in the literature, but no resource provides a current overview. This paper systematically surveys the state-of-the-art in formal specification and verification for autonomous robotics. Specially, it identifies and categorises the challenges posed by, the formalisms aimed at, and the formal approaches for the specification and verification of autonomous robotics. Introduction, Methodology and Related WorkAn autonomous system is an artificially intelligent entity that makes decisions in response to input, independent of human interaction. Robotic systems are physical entities that interact with the physical world. Thus, we consider an autonomous robotic system as a machine that uses Artificial Intelligence (AI), has a physical presence in and interacts with the real world. They are complex, inherently hybrid, systems, combining both hardware and software; they often require close safety, legal, and ethical consideration. Autonomous robotics are increasingly being used in commonplace-scenarios, such as driverless cars [68], pilotless aircraft [176], and domestic assistants [174,60].While for many engineered systems, testing, either through real deployment or via simulation, is deemed sufficient; the unique challenges of autonomous robotics, their dependence on sophisticated software control and decision-making, and their increasing deployment in safety-critical scenarios, require a stronger form of verification. This leads us towards using formal methods, which are mathematically-based techniques for the specification and verification of software systems, to ensure the correctness of, and provide sufficient evidence for the certification of, robotic systems.We contribute an overview and analysis of the state-of-the-art in formal specification and verification of autonomous robotics. §1.1 outlines the scope, research questions and search criteria for our survey. §1.2 describes related work concerning formal methods for robotics and differentiates them from our work. We recognise the important role that middleware architectures and, non-and semi-formal techniques have in the development of reliable robotics and we briefly summarise some of these techniques in §2. The specification and verification challenges raised by autonomous robotic systems are discussed next: §3 describes the challenges of their context (the external challenges) and §4 describes the challenges of their organisation (the internal challenges). §5 discusses the formalisms used in the literature for specification and verification of autonomous robotics. §6 characterises the approaches to formal specification and verification of autonomous robotics found in the li...

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Section: Logics 6 32mentioning

confidence: 99%

Section: Summary Of Formalisms For Robotic Systemsmentioning

confidence: 99%

Section: References Totalmentioning

confidence: 99%

Section: Runtime Monitoringmentioning

confidence: 99%

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Formal Specification and Verification of Autonomous Robotic Systems

et al. 2019

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“…Other authors provide methods to identify safety invariants either from a hazard analysis [21] or from execution traces [11]. Some specify safety strategies in a DSL (Domain Specific Language) in order to generate code [3], [10]. But none of them offers a complete approach to identify invariants from hazards and formally derive the safety strategies.…”

Section: Related Workmentioning

confidence: 99%

Tuning Permissiveness of Active Safety Monitors for Autonomous Systems

Masson

Guiochet

Waeselynck

et al. 2018

Lecture Notes in Computer Science

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Abstract. Robots and autonomous systems have become a part of our everyday life, therefore guaranteeing their safety is crucial. Among the possible ways to do so, monitoring is widely used, but few methods exist to systematically generate safety rules to implement such monitors. Particularly, building safety monitors that do not constrain excessively the system's ability to perform its tasks is necessary as those systems operate with few human interventions. We propose in this paper a method to take into account the system's desired tasks in the specification of strategies for monitors and apply it to a case study. We show that we allow more strategies to be found and we facilitate the reasoning about the trade-off between safety and availability.

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Embedding Online Runtime Verification for Fault Disambiguation on Robonaut2

Kempa

Zhang

Jones

et al. 2020

Lecture Notes in Computer Science

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Robonaut2 (R2) is a humanoid robot onboard the International Space Station (ISS), performing specialized tasks in collaboration with astronauts. After deployment, R2 developed an unexpected emergent behavior. R2's inability to distinguish between knee-joint faults (e.g., due to sensor drift versus violated environmental assumptions) began triggering safety-preserving freezes-in-place in the confined space of the ISS, preventing further motion until a ground-control operator determines the root-cause and initiates proper corrective action. Runtime verification (RV) algorithms can efficiently disambiguate the temporal signatures of different faults in real-time. However, no previous RV engine can operate within the limited available resources and specialized platform constraints of R2's hardware architecture. An attempt to deploy the only runtime verification engine designed for embedded flight systems, R2U2, failed due to resource constraints. We present a significant redesign of the core R2U2 algorithms to adapt to severe resource and certification constraints and prove their correctness. We further define an optimization enabled by our new algorithms and implement the new version of R2U2. We encode specifications describing real-life faults occurring onboard Robonaut2 using Mission-time Linear Temporal Logic (MLTL) and detail our process of specification debugging, validation, and refinement. We deployed this new version of R2U2 on Robonaut2, demonstrating successful real-time fault disambiguation and mitigation triggering of R2's knee-joint faults without false positives.

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ROSRV: Runtime Verification for Robots

Cited by 85 publications

References 4 publications

Formal Specification and Verification of Autonomous Robotic Systems

Formal Specification and Verification of Autonomous Robotic Systems

Tuning Permissiveness of Active Safety Monitors for Autonomous Systems

Embedding Online Runtime Verification for Fault Disambiguation on Robonaut2

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