Reliability and Safety of Autonomous Systems Based on Semantic Modelling for Self-Certification

Abstract

A novel modelling paradigm for online diagnostics and prognostics for autonomous systems is presented. A model for the autonomous system being diagnosed is designed using a logic-based formalism. The model supports the run-time ability to verify that the autonomous system is safe and reliable for operation within a dynamic environment. The paradigm is based on the philosophy that there are different types of semantic relationships between the states of different parts of the system. A finite state automaton is devised for each sensed component and some of the non-sensed components. To capture the interdependencies of components within such a complex robotic platform, automatons were related to each other by semantic relationships. Modality was utilised by the formalism to abstract the relationships and to add measures for the possibility and uncertainty of the relationships. The complexity of the model was analysed to evaluate its scalability and applicability to other systems. The results demonstrate that the complexity is not linear and a computational time of 10 ms was required to achieve run-time diagnostics for 2200 KB of knowledge for complex system interdependences. The ability to detect and mitigate hardware related failures was demonstrated within a confined space autonomous operation. Our findings provide evidence of the applicability of our approach for the significant challenge of run-time safety compliance and reliability in autonomous systems.

Symbiotic System of Systems Design for Safe and Resilient Autonomous Robotics in Offshore Wind Farms

“…These capabilities directly impact the real-time safety case, reliability and resilience of a robotic system. The developed ontology can be applied to several tasks that humans and robots can perform cooperatively within a defined infrastructure, mission profile and environment [70].…”

“…For each critical part of the system in the AI-driven ontology, a diagnosis automaton is constructed, such as motor, battery, motor driver, wheel, single component or an integrated device, whether sensed or non-sensed. A segment of a system might have its own distinctive states to ensure that rules are in place to govern C 3 and the safety of the robotic platform [70].…”

“…There are two models namely, "is-type-of" and "is-linked-to" or "is-connected-to". For example, "x isconnected-to y" [70].…”

“…The logic behind the binary relationship is expressed in the ontology to enable C 3 across the subcomponents in the SSOSA. A detailed formalism of the logic can be found in Zaki et al [70].…”

“…Three binary relations: 'causality', 'implication', and 'prevention' are combined in modality to show the degree of certainty in the relationship [70]. For example, x might-cause y, x must-cause y. Modal verbs combined with those relations include:…”