robotics and integrated formal methods: necessity meets ... · robotics and integrated formal...
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Robotics and Integrated Formal Methods:Necessity meets Opportunity
Marie Farrell, Matt Luckcuck, and Michael Fisher
Department of Computer Science, University of Liverpool, UK
26th of September 2018
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Robotic System Properties
Multi-dimensional:I Embedded System
I Cyber-Physical SystemI Real-Time SystemI Hybrid SystemI Adaptive SystemI Autonomous System
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Robotic System Properties
Multi-dimensional:I Embedded SystemI Cyber-Physical System
I Real-Time SystemI Hybrid SystemI Adaptive SystemI Autonomous System
Matt Luckcuck Robotics and iFM 2/31
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Robotic System Properties
Multi-dimensional:I Embedded SystemI Cyber-Physical SystemI Real-Time System
I Hybrid SystemI Adaptive SystemI Autonomous System
Matt Luckcuck Robotics and iFM 2/31
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Robotic System Properties
Multi-dimensional:I Embedded SystemI Cyber-Physical SystemI Real-Time SystemI Hybrid System
I Adaptive SystemI Autonomous System
Matt Luckcuck Robotics and iFM 2/31
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Robotic System Properties
Multi-dimensional:I Embedded SystemI Cyber-Physical SystemI Real-Time SystemI Hybrid SystemI Adaptive System
I Autonomous System
Matt Luckcuck Robotics and iFM 2/31
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Robotic System Properties
Multi-dimensional:I Embedded SystemI Cyber-Physical SystemI Real-Time SystemI Hybrid SystemI Adaptive SystemI Autonomous System
Matt Luckcuck Robotics and iFM 2/31
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What is an Integrated Formal Method
Integrated Formal Methods (iFM)I Integrating multiple formal methods
I Loose: cooperating formalismsI Tight: single formalism
I Integration of formal and non-formal methodsI e.g. Graphical notation
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Our Position
Necessity meets Opportunity
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Our Position
Necessity meets OpportunityI Based on our previous survey work. . .
I Available: https://arxiv.org/abs/1807.00048I Robotics:
I Present particular challengesI Require integration of diverse formal methods
I Formal Methods Benefits:I Real-World catalyst for integration research
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Outline
Next. . .I Highlight four robotics challenges
I EnvironmentI CertificationI Multi-Robot SystemsI Reconfiguration
I Discuss integrated formal approachesI CurrentI Direction
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Challenge One:Modelling the Physical Environment
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Modelling the Physical Environment
Challenge:I How to specify and verify the behaviour of the robot working in a dynamic and often
unknown environment
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Modelling the Physical Environment
Current Approaches:I Ignore the environment!aI Assume that the environment it is static and known, prior to deploymentb
I Use predicates representing sensor data to abstract away from the environmentc
aSavas Konur, Clare Dixon, and Michael Fisher. “Analysing Robot Swarm Behaviour via Probabilistic ModelChecking”. In: Robotics and Autonomous Systems 60.2 (2012), pp. 199–213.
bSalar Moarref and Hadas Kress-Gazit. “Decentralized control of robotic swarms from high-level temporallogic specifications”. In: Int. Symp. Multi-Robot Multi-Agent Syst. IEEE, 2017.
cMichael Fisher, Louise A Dennis, and Matt Webster. “Verifying Autonomous Systems”. In: Commun. ACM56.9 (2013), pp. 84–93.
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Modelling the Physical Environment
Formal Methods must bridge the reality gap:
I Model the environment usingI e.g. Probabilistic Temporal Logic (PTL)a
I Monitor the environmentI e.g. Timed Automatab
aM. Webster et al. “Toward Reliable Autonomous Robotic Assistants Through Formal Verification: A CaseStudy”. In: IEEE Transactions on Human-Machine Systems 46.2 (2016), pp. 186–196.
bAdina Aniculaesei et al. “Towards the Verification of Safety-critical Autonomous Systems in DynamicEnvironments”. In: Electron. Proc. Theor. Comput. Sci. 232 (2016), pp. 79–90.
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Challenge Two:Trust and Certification Evidence
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Trust and Certification Evidence
Operating Context1. Saftey-Critical e.g. nuclear/aerospace
2. Require public trust
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Trust and Certification Evidence
Challenges:I Formal verification must provide appropriate evidence for
I Public TrustI Regulator Certification
I Which formal methods are suitable?I What evidence is needed?I What type of robotic system?
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Trust and Certification Evidence
Current Approaches:
I Automatic generation of safety caseI e.g. AUTOCERT for a pilotless aircrafta
I Formalising and verifying domainspecific rulesI e.g. Isabelle/HOL to formalise rules for
vehicle overtakingb
aEwen Denney and Ganesh Pai. “Automating the assembly of aviation safety cases”. In: IEEE Transactions onReliability 63.4 (2014), pp. 830–849.
bAlbert Rizaldi et al. “Formalising and monitoring traffic rules for autonomous vehicles in Isabelle/HOL”. In:Integr. Form. Methods. Vol. 10510. LNCS. 2017, pp. 50–66.
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Challenge Three:Multi-Robot Systems
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Multi-Robot Systems
Types of Multi-Robot SystemsI Homogeneous robots: SwarmsI Heterogeneous robots: Teams
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Multi-Robot Systems
Types of Multi-Robot SystemsI Homogeneous robots: SwarmsI Heterogeneous robots: Teams
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Multi-Robot Systems
Types of Multi-Robot SystemsI Homogeneous robots: SwarmsI Heterogeneous robots: Teams
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Multi-Robot Systems: Swarms
Challenges:I Linking formal specifications
I macroscopic (whole swarm) levelI microscopic (individual robots) level
I State explosion when model-checking large swarms.
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Multi-Robot Systems: Swarms
Current Approaches:I Temporal logics
I Specify and verify swarms at different levels of abstractiona
I Abstractions the mitigate state explosionb
I Symmetry reductionI Counting abstraction
aAlan F.T. Winfield et al. “On formal specification of emergent behaviours in swarm robotic systems”. In: Int.J. Adv. Robot. Syst. 2.4 (2005), pp. 363–370.
bSavas Konur, Clare Dixon, and Michael Fisher. “Analysing Robot Swarm Behaviour via Probabilistic ModelChecking”. In: Robotics and Autonomous Systems 60.2 (2012), pp. 199–213.
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Multi-Robot Systems: Teams
Challenge:I Linking specification
I macroscopic (whole team) levelI microscopic (individual robots) level
I Heterogeneity. . .
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Challenge Four:Adaptation, Reconfigurability, and Autonomy
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Adaptation, Reconfigurability and Autonomy
ChallengeI Specifying self-adaptive systems
I Respond to changes in the environmentI Specifying reconfigurable systems
I Decide on how best to reconfigure themselvesI Specifying reconfigurability
I Autonomous decision-making
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Adaptation, Reconfigurability and Autonomy
Current Approaches:I Model-checking at runtime for self-adaptive systemsa
I Agent-based systems to model autonomyI Verified using temporal logics and model-checkersI e.g. probabilistic model-checking of autonomous mine detector robotb
aBetty H.C. Cheng et al. “Using models at runtime to address assurance for self-adaptive systems”. In:[email protected]. Vol. 8378. LNCS. 2014, pp. 101–136.
bPaolo Izzo, Hongyang Qu, and Sandor M. Veres. “A stochastically verifiable autonomous controlarchitecture with reasoning”. In: Conf. Decis. Control (2016), pp. 4985–4991.
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Integrated Formal Approaches to Robotic Challenges
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Why iFM?
Robotic Challenges. . .1 Environment
2 Certification Evidence3 Multi-Robot Systems4 Reconfigurable/Autonomous
Systems
iFM Can. . .
1 Combine static and dynamic models2 Provide robust evidence3 Link macro- and micro- behaviour4 Describe complex configuration and
autonomy
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Why iFM?
Robotic Challenges. . .1 Environment
2 Certification Evidence3 Multi-Robot Systems4 Reconfigurable/Autonomous
Systems
iFM Can. . .1 Combine static and dynamic models
2 Provide robust evidence3 Link macro- and micro- behaviour4 Describe complex configuration and
autonomy
Matt Luckcuck Robotics and iFM 24/31
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Why iFM?
Robotic Challenges. . .1 Environment2 Certification Evidence
3 Multi-Robot Systems4 Reconfigurable/Autonomous
Systems
iFM Can. . .1 Combine static and dynamic models
2 Provide robust evidence3 Link macro- and micro- behaviour4 Describe complex configuration and
autonomy
Matt Luckcuck Robotics and iFM 24/31
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Why iFM?
Robotic Challenges. . .1 Environment2 Certification Evidence
3 Multi-Robot Systems4 Reconfigurable/Autonomous
Systems
iFM Can. . .1 Combine static and dynamic models2 Provide robust evidence
3 Link macro- and micro- behaviour4 Describe complex configuration and
autonomy
Matt Luckcuck Robotics and iFM 24/31
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Why iFM?
Robotic Challenges. . .1 Environment2 Certification Evidence3 Multi-Robot Systems
4 Reconfigurable/AutonomousSystems
iFM Can. . .1 Combine static and dynamic models2 Provide robust evidence
3 Link macro- and micro- behaviour4 Describe complex configuration and
autonomy
Matt Luckcuck Robotics and iFM 24/31
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Why iFM?
Robotic Challenges. . .1 Environment2 Certification Evidence3 Multi-Robot Systems
4 Reconfigurable/AutonomousSystems
iFM Can. . .1 Combine static and dynamic models2 Provide robust evidence3 Link macro- and micro- behaviour
4 Describe complex configuration andautonomy
Matt Luckcuck Robotics and iFM 24/31
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Why iFM?
Robotic Challenges. . .1 Environment2 Certification Evidence3 Multi-Robot Systems4 Reconfigurable/Autonomous
Systems
iFM Can. . .1 Combine static and dynamic models2 Provide robust evidence3 Link macro- and micro- behaviour
4 Describe complex configuration andautonomy
Matt Luckcuck Robotics and iFM 24/31
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Why iFM?
Robotic Challenges. . .1 Environment2 Certification Evidence3 Multi-Robot Systems4 Reconfigurable/Autonomous
Systems
iFM Can. . .1 Combine static and dynamic models2 Provide robust evidence3 Link macro- and micro- behaviour4 Describe complex configuration and
autonomy
Matt Luckcuck Robotics and iFM 24/31
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Current Integrated Formal Approaches to Robotic Challenges
AdoptionI Event-B and PRISM
I Reconfigurable architecture for an on-board satellite systemI CSP ‖ B
I Vehicle platooningI AJPF, UPPAAL, and Spatial Calculus
I Platoon joining and leaving procedures for a driverless carI FSP and πADL for safety
I Multi-agent systemsI RoboChart
I State Charts with CSP underneath
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Future Integrated Formal Approaches to Robotic Challenges
Complementary methodsI Benefits of two formal methods
I e.g. model-checking and proof-based methodsI Benefits of formal method and existing non-formal method
I Robust (auto-generated?) evidence for certification
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Future Integrated Formal Approaches to Robotic Challenges
Heterogeneous ModelsI Aimed at ROS, Swarms, Teams, etcI Link abstract specifications of nodes. . .I . . .with the specification of the nodeI Convert between verification toolsI Challenges:
I Different Levels of AbstractionI Different formalisms?I Different properties?I Consistency of properties and information?
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Future Integrated Formal Approaches to Robotic Challenges
Heterogeneous ModelsI Aimed at ROS, Swarms, Teams, etcI Link abstract specifications of nodes. . .I . . .with the specification of the node (which may be heterogeneous)I Convert between verification toolsI Challenges:
I Different Levels of Abstraction
I Different formalisms?I Different properties?I Consistency of properties and information?
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Future Integrated Formal Approaches to Robotic Challenges
Heterogeneous ModelsI Aimed at ROS, Swarms, Teams, etcI Link abstract specifications of nodes. . .I . . .with the specification of the nodeI Convert between verification toolsI Challenges:
I Different Levels of AbstractionI Different formalisms?
I Different properties?I Consistency of properties and information?
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Future Integrated Formal Approaches to Robotic Challenges
Heterogeneous ModelsI Aimed at ROS, Swarms, Teams, etcI Link abstract specifications of nodes. . .I . . .with the specification of the nodeI Convert between verification toolsI Challenges:
I Different Levels of AbstractionI Different formalisms?I Different properties?
I Consistency of properties and information?
Matt Luckcuck Robotics and iFM 27/31
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Future Integrated Formal Approaches to Robotic Challenges
Heterogeneous ModelsI Aimed at ROS, Swarms, Teams, etcI Link abstract specifications of nodes. . .I . . .with the specification of the nodeI Convert between verification toolsI Challenges:
I Different Levels of AbstractionI Different formalisms?I Different properties?I Consistency of properties and information?
Matt Luckcuck Robotics and iFM 27/31
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Necessity meets Opportunity
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Necessity meets Opportunity
Who benefits?
Robotics: integration of formal methods into the development process and potentialsolutions to the four challenges identified earlier.
iFM: a set of real-world targets that will help to advance the field in new andexciting directions.
Matt Luckcuck Robotics and iFM 29/31
![Page 48: Robotics and Integrated Formal Methods: Necessity meets ... · Robotics and Integrated Formal Methods: Necessity meets Opportunity Marie Farrell, Matt Luckcuck, and Michael Fisher](https://reader034.vdocuments.mx/reader034/viewer/2022042311/5ed906906714ca7f476901fe/html5/thumbnails/48.jpg)
Necessity meets Opportunity
Who benefits?Robotics: integration of formal methods into the development process and potential
solutions to the four challenges identified earlier.
iFM: a set of real-world targets that will help to advance the field in new andexciting directions.
Matt Luckcuck Robotics and iFM 29/31
![Page 49: Robotics and Integrated Formal Methods: Necessity meets ... · Robotics and Integrated Formal Methods: Necessity meets Opportunity Marie Farrell, Matt Luckcuck, and Michael Fisher](https://reader034.vdocuments.mx/reader034/viewer/2022042311/5ed906906714ca7f476901fe/html5/thumbnails/49.jpg)
Necessity meets Opportunity
Who benefits?Robotics: integration of formal methods into the development process and potential
solutions to the four challenges identified earlier.
iFM: a set of real-world targets that will help to advance the field in new andexciting directions.
Matt Luckcuck Robotics and iFM 29/31
![Page 50: Robotics and Integrated Formal Methods: Necessity meets ... · Robotics and Integrated Formal Methods: Necessity meets Opportunity Marie Farrell, Matt Luckcuck, and Michael Fisher](https://reader034.vdocuments.mx/reader034/viewer/2022042311/5ed906906714ca7f476901fe/html5/thumbnails/50.jpg)
More Information
Motivating Survey:Luckcuck, M., Farrell, M., Dennis, L., Dixon, C., & Fisher, M. (2018). Formal Specification andVerification of Autonomous Robotic Systems: A Survey. arXiv preprint arXiv:1807.00048.
Robotics and Artificial Intelligence in Hazardous Environments:I RAIN: https://rainhub.org.uk/I ORCA: https://orcahub.org/I FAIR-SPACE: https://www.fairspacehub.org/
Matt Luckcuck Robotics and iFM 30/31
![Page 51: Robotics and Integrated Formal Methods: Necessity meets ... · Robotics and Integrated Formal Methods: Necessity meets Opportunity Marie Farrell, Matt Luckcuck, and Michael Fisher](https://reader034.vdocuments.mx/reader034/viewer/2022042311/5ed906906714ca7f476901fe/html5/thumbnails/51.jpg)
Questions?
Matt Luckcuck Robotics and iFM 31/31