Beyond the state of the art
At the heart of the SESAME project innovations were a model-based approach where models are automatically composable and also algorithmically analysable at both design time and runtime. SESAME further advanced multi-robot systems engineering by providing:
+ Domain-specific languages that hide the complexity and intricacies of robotic simulators and platforms
+ Machine Learning based libraries of well-designed scenarios that are adaptable and reusable across applications
+ Design-time analysis of safety and security via composition, reuse and automated analysis
+ Novel safety and security assurance achieved by shifting part of the assurance to runtime
+ Seamless (re)configuration at design and at runtime to easily adapt to changing needs and operating environments
SESAME builds on a novel and advanced synthesis of the state-of-the-art in model-based development, nature-inspired technologies, and AI data-driven techniques. Model-based techniques were used to capture pertinent engineering knowledge and assumptions about MRS operation, failures and their effects, in verifiable and executable at runtime models that can be used to assess, verify and ensure security and safety.
Two of the key technology advances that developed in the project were:
+ Executable Scenarios (ExSce) are model-based narrative descriptions of robotic missions guiding the design, development, configuration and deployment of multi-robot systems.
+ Executable Digital Dependability Identities (EDDI) are model-based artefacts spanning the multi-robot system lifecycle that carry verifiable dependability models of their reference robotic systems produced at design-time based on ExSce, capturing safety and security hazards, their causes, effects and possible corrective actions.
Expected Impact
SESAME technologies will deliver to European industries substantial benefits for MRS in the following areas:
+ Accuracy – improved robot self-localisation accuracy using sensor-fusion from multiple robots
+ Robustness – collaborative intelligence enables robotic teams to cope with severe failures
+ Efficiency – perception-aware trajectory planning reduces time for MRS task execution
+ Safety – improved coverage of hazards related to emergent behaviour and uncertainty
+ Security – increased coverage of cyber risks and extended robotics security assurance
+ Adaptability – MRS automatically adapt to observed conditions providing substantial performance gains
+ Quality – intelligent testing of operational designs quickly uncovers corner cases that could violate safety or security requirements
SESAME will lower the development costs and deliver greater assurance of the safety, security and dependability of multi-robot systems for wide range of European industries, which will be demonstrated and validated through five novel industrial applications from the Healthcare, Infrastructure Inspection & Maintenance, Smart Agri-Food and Agile Manufacturing sectors.
