The following early technical reports addressing Multi-Robot Systems (MRS) development and deployment technologies were completed during the first half of the project and have been made publicly available. Also available are published technical papers and journal articles by visiting our News section and clicking the Tag of interest. Click on any of the reports to download the document.
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1. Sensor Fusion and Collaborative Intelligence
Specification of MRS Capabilities
A novel concept of stratagem, which encapsulates the capabilities of individual robots and robotic teams.
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Several model identification techniques are developed to be used at run-time by a robot to identify the dynamic and kinematic model of itself or other robots in MRS.
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Perception and collaborative sensor fusion mechanisms that allow robots to comprehend their environment accurately.
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Multi-Robot Monitoring Online Trajectory Generation
Online trajectory generation approach that minimises uncertainty of a group of robots while maximising their efficiency in performing specific tasks.
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Multi-Robot Collaborative Rescue Mission
Novel architecture to generate trajectories of a collaborative MRS.
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Experience-Based Planning and Collaborative Intelligence of MRS
Collaborative intelligence of MRS through the ability to share and compose experiences of individual robots with other robots.
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2. Executable Scenarios and System Modelling
MRS Design Concept and Methodology
Scientific foundations, concepts and principles of the proposed Executable Scenario (ExSce) methodology for engineering dependable MRS.
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Executable Scenario Management
Enables the storage and querying of provenance data for scenario executions.
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Executable Scenarios Workbench (Final Version)
Three tools conforming to the methodology of scenario-based development of multi-robot applications and construction of scenarios.
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Public Repository of Executable Scenarios
Metamodels and models developed to support the Executable Scenarios Workbench.
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3. Safety-Targeted Executable Digital Dependability Identities
Safety Analysis Concept and Methodology for EDDI development
Safety analysis concept and methodology for developing safe and secure MRS integrating the key concepts of the EDDI.
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Safety-Targeted and Security-Targeted ODE and EDDI specification
Specification of the Open Dependability Exchange (ODE) meta model and the new safety and security modifications and extensions for MRS driven EDDIs.
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Safety-Security Co-Engineering Framework
A combined safety/security co-engineering framework based on the ODE, the metamodel that serves as a basis for the EDDI dependability management concept.
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Tools for Automated Safety Analysis of MRS and for Production of EDDIs (Final Version)
Existing safety analysis tools are utilised to create appropriate system models and safety artefacts, which are converted to ODE-compliant models via tool adapters and model converters.
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4. Security-Targeted Executable Digital Dependability Identities
Security Analysis Concept and Methodology for EDDI development
Security assessment concept and methodology that will be used in the SESAME project.
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Tools for Automated Security Analysis of MRS and for Production of EDDIs
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Technologies and techniques for adapting EDDI and associated infrastructure to facilitate the deployment and integration of EDDIs to reduce effort and resource investment.
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Techniques and tools that have been adopted for securing the EDDIs and ensure no additional attack surfaces are created and no additional attack types are utilized.
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5. MRS-Executable Digital Dependability Identities Quality Assurance
Assurance of Data-Driven and Learning Components of EDDIs
Introduces DeepKnowledge providing a novel test adequacy criterion for testing DL-based systems and providing insights by analysing the generalisation behaviour of Deep Neural Networks (DNN) models under domain shift.
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Simulation-Based Testing Methodology for EDDIs
Methodology for simulation-based testing is presented based on the utilisation of a domain-specific language (DSL) to model the space of potential fuzz testing operations upon the MRS.
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Tools for Automated Quality Assurance of EDDI-Supported MRS (Final Version)
Details on deploying the simulation-based testing platform informed by the safety analysis that underlies the construction of the EDDIs, and the DeepKnowledge framework used to evaluate the quality of the EDDIs.
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Recommendations for EDDI Repair and Hardening
Tool-supported methodology for hardening and repairing DLs used for MRS that leverages the dependability assurance analysis results.
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Quality Assurance of EDDI-Enabled MRS Using Digital Twins
Digital twin technology that provides simulation-based tools with data from deployed MRS to perform failure prediction and almost real-time validation and verification of system adaptations.
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Multi-Stage Quality Assurance Methodology for EDDI-Supported MRS
Integrated methodology for the transition between simulation-based testing and
physical testing of MRS systems.
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6. Runtime MRS Dependability Management
Runtime Safety and Security Concept - EDDI Runtime Model Specification
Address dependability of MRS through Executable Digital Dependability Identity (EDDI) runtime components.
Tools for Generation of Runtime EDDIs
Explains the toolchain for the generation of runtime EDDIs. Platform independent and dependent software components are semi-automatically generated, which contain functionality to dynamically supervise dependability properties of an MRS.
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Runtime Safety and Security Concept - EDDI-based MAS and Communication
Addresses how RunTime EDDIs can be designed and deployed as Multi-Agent Systems (MAS) to collaborate towards MRS dependability assurance during operation.
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Open-Source Software Components for Explainable EDDIs
Tools developed and upgraded for the purpose of explaining EDDI state and/or behaviour.
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7. Installation and Deployment
Describes the integrated versions of the SESAME components, reports on main features and installation/customization guidelines. Provides descriptions of the integrated platform architecture with a detailed description of all integrated components, and includes the basic workflow of the SESAME tools and components.
