Failure of robotic software may cause catastrophic damages. In order to establish a higher level of trust in robotic systems, formal methods are often proposed. However, their applicability to the functional layer of robots remains limited because of the informal nature of specifications, their complexity and size. In this paper, we formalize the robotic framework G en oM3 and automatically translate its components to UPPAAL-SMC, a real-time statistical model checker. We apply our approach to verify properties of interest on a real-world autonomous drone navigation that does not scale with regular UPPAAL.
Software is an essential part of robotic systems. As robots and autonomous systems are more and more deployed in human environments, we need to use elaborate validation and verification techniques in order to gain a higher level of trust in our systems. This motivates our determination to apply formal verification methods to robotics software. In this paper, we describe our results obtained using model-checking on the functional layer of an autonomous robot. We implement an automatic translation from GenoM, a robotics model-based software engineering framework, to the formal specification language Fiacre. This translation takes into account the semantics of the robotics middleware. TINA, our model-checking toolbox, can be used on the synthesized models to prove real-time properties of the functional modules implementation on the robot. We illustrate our approach using a realistic autonomous navigation example.
Software constitutes a major part of the development of robotic and autonomous systems and is critical to their successful deployment in our everyday life. Robotic software must thus run and perform as specified. Since most of these systems are used in a hard real-time context, the schedulability of their tasks is a crucial property. In this work, we propose to use formal methods to check whether the tasks of a robotic application are schedulable with respect to a given hardware platform. For this, we automatically translate functional components specified in GenoM into FIACRE, a formal language for timed systems. The generated models integrate realistic real-time schedulers based on the FCFS and the SJF cooperative policies. We use then the model-checker TINA to assert schedulability properties. We carry out experiments on a real robotic system, namely a quadcopter flight controller. We demonstrate that, on its actual hardware, schedulability properties can be formally expressed and verified. We give examples on how we can check other important behavioral and timed properties on the same synthesized models.
Formal verification of robotic functional components is extremely important. Indeed, with the growing involvement of autonomous systems in everyday life, we may no longer rely on classical testing and simulation to establish our trust in them. However, the formalization of such systems is challenging considering the various existing formalisms and their respective advantages/drawbacks. One may express more easily in one formalism and verify more easily in another depending on the aspects/properties they are modeling/verifying. Furthermore, both the reusability of the formalization and the scalability of the obtained formal models are crucial elements in the verification process. In this paper, we present modeling concurrency aspects of robotic functional components in Time Petri Nets, Timed Automata and Timed Automata extended with urgencies. Formal models are automatically generated and verification is conducted on each of them. Both the expressiveness of the formalisms and scalability of the obtained models are evaluated and future directions are consequently outlined.
The challenges of deploying robots and autonomous vehicles call for further efforts to bridge the gap between the robotics, the real-time systems and the formal methods communities. Indeed, with robots being more and more involved in costly missions and contact with humans, a rigorous formal verification of their behavior in the presence of various real-time constraints is crucial. In order to increase our trust in its results, such verification should be carried out on models that are as close as possible to reality, and thus take into account hardware and OS specificities such as the number of cores provided by the robotic platform and the scheduling policy. In this paper, we propose a novel binary-search-inspired technique that allows to extend timed automata models of robotic specifications with dynamic-priority schedulers. Given a number of cores, the extended models can then be checked against various real-time and behavioral properties, including schedulability, within the same model checking framework. Our technique is implemented in an automatic translation from a robotic framework to UPPAAL, and evaluated on a real robotic case study, where it shows a significant gain in scalability as opposed to the counting technique used in the literature.
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