Toolbox The COGNIMAN Solutions Cluster brings together technology providers, industrial validation environments and end-users to accelerate the adoption of advanced manufacturing solutions. At its core is the COGNIMAN Toolbox, a set of practical components and methods developed within the project to address key challenges in modern production.

Each solution has been designed following a human-centric approach, ensuring that technologies enhance worker safety, usability and productivity.

The toolbox components are developed and validated on-site in real industrial settings by technology providers, ensuring their relevance and readiness for practical deployment. Through on-request access, the cluster makes these innovations available to SMEs, startups, universities, companies, operators and researchers, enabling them to explore, test and adopt advanced manufacturing capabilities.

COGNIMAN Toolbox Components

Physical Twin

The physical twin represents the actual physical object, process, or system within the real world. This layer includes physical machinery, equipment, devices, and any other tangible components that are part of the manufacturing environment. Sensors and actuators embedded in these physical assets collect real-time data, which serves as the basis for creating and updating the digital twin.

Spinnaker ROS2 Camera Driver for Blackfly Camera Sensors

AGV Camera sensor (GOIMEK pilot)

Livox ROS 2 Driver for Lidar Sensors

AGV Lidar sensor (GOIMEK pilot)

DepthAI ROS2 Camera Driver for OAK Camera Sensors

OAK Camera sensor (DepthAI ROS Integration)

Ouster ROS 2 Driver for Lidar Sensors

AGV Ouster sensor (GOIMEK pilot)

Video stream acquisition

The system must be able to acquire a video of the stock (ABS Pilot)

Data Layer

The data layer serves as the foundation for the entire digital twin ecosystem. It encompasses the collection, storage, and management of raw data generated by sensors and other data sources associated with the physical twin. This data can include measurements, sensor readings, operational parameters, environmental conditions, and more. Proper data processing and storage are crucial to ensure accurate and reliable digital twin representations.

Database Design for Manufacturing Data

The system provides a unified interface for interacting with different database backends (PostgreSQL, MySQL, SQLite) ...

Aruco Marker Detection

Detects ArUco markers from an RGB stream in ROS 2 and provides real-time pose data.

Digitization data recorder

Manages data from a digitization process (GOIMEK pilot)

Semantic Map Uploader

Uploads and manages semantic maps in a centralized cloud storage

Pose Transformation

Transforms pose coordinates between frames using a transformation tree

Touch probing data recorder

Manages data from a touch probing location process (GOIMEK pilot)

Digital Twin Representation

The heart of the architecture is the digital twin itself. This layer is a virtual representation of the physical twin, constructed using the real-time data collected from sensors and combined with relevant contextual information. The digital twin accurately mirrors the behaviour, characteristics, and conditions of its physical counterpart through modeling, such as Artificial Intelligence (AI), Graph based modeling, etc. It enables simulations, analysis, and monitoring, allowing for predictive insights and informed decision-making.

SINDIT

Knowledge Graph Based Digital Twin Framework.

Clearpath Robotic Simulator

Digital Twin Clearpath Robotic Simulator

Gazebo Robotic Simulator

Digital Twin Robotic Simulator

Real-Time ROS2 Lichtblick Visualizer

Real-Time viewer of ROS2 in a web-based fully customizable user interface

Real-Time ROS2 Board

Real-Time viewer of ROS2 in a web-based board

Batch identification

The system must be able to acquire the batch 'code' at least in the 90% of cases (ABS Pilot)

Implementation of 2D map

Develop a 2D map that contains: Ground clearance of the bar (y); Abscissa of the bar (X) (ABS Pilot)

Real-Time ROS2 Log Bag Player

Real-Time Log Player for ROS2

Position for different bar dimensions and sections

The system must be able to acquire batch position for different bar dimensions and sections (ABS Pilot)

Digital Twin AM Printing Process

Additive Manufacturing Quality Assessment using Digital Twin

Service Layer

The service layer encapsulates the functionalities and services that leverage the capabilities of the digital twin. This layer includes various algorithms, models, simulations, and analytic that use the data from the digital twin to generate insights, predictions, and optimization strategies. It is responsible for translating raw data into actionable information and facilitating interactions between different layers of the architecture.

Frame calculation based on touch probing

Calculates the new part frame based on the data from the touch probing and deburring planning (GOIMEK pilot)

Path adaptation based on digitization data

Adapts the path points of the trajectory based on digitization data (GOIMEK pilot)

Path points to robot trajectory

Generates robot trajectory programs for a Staubli robot based on the pathpoints (GOIMEK pilot)

Orbital Navigation Service

Orbital Navigation for autonomous robots

Autonomous Deburring

Embedded software for autonomous deburring management (GOIMEK pilot)

Deburring Planning

Embedded software to plan deburring trajectories (GOIMEK pilot)

Navigation Map Generator

Generation of navigation map (2D) from geometric map (3D)

Navigation Route Generator

Generation of Navigation Route

Semantic Map Generator

Generation of geometric & semantic map (3D) from previously recorded data

Autonomous Navigation Service

Autonomous Navigation Library

Semantic Map Data Recorder

Records ROS 2 data streams for semantic map generation

BlackBox Service

BlackBox service for auditing

Frequency update of the 2D map

The frequency of update of the map must be at least once a day (ABS Pilot)

Safety rules support (triangle)

The system must be able to recognize the shape of the bar (round), wedges, height, etc. (ABS Pilot)

Safety rules validation (square section)

The system must be able to recognize the shape of the bar (square), height, etc. (ABS Pilot)

Job Card Extractor

Automatically digitize paper job cards into structured data — eliminate manual data entry

Barcode Detection and Batch Positioning

Automatically identify and map stacked objects from video footage into a structured digital layout

Top-View Safety Evaluation

Automated drone-based safety assessment of material stacks in industrial warehouses

User Interface

The user interface layer provides a means for human interaction with the digital twin ecosystem. It includes interfaces such as graphical user interfaces (GUIs), dashboards, augmented reality (AR) or virtual reality (VR) applications, and other visualization tools. This layer allows users, including operators, engineers, and managers, to monitor the state of the digital twin, access insights, and make informed decisions.

Manufacturing Assistant System (MAS)

Manage metal 3D printing end-to-end — from job prep to robotic post-processing and quality

Warehouse Logistic Assistant

Web-based warehouse assistant with digital twin visualization, batch tracking, and AI safety evaluation

Connectivity and Integration

The connectivity and integration layer ensures seamless communication between the various components of the architecture. This layer facilitates data exchange between the physical twin, data layer, digital twin, service layer, user interface, and external systems. It might involve technologies such as Internet of Things (IoT) protocols, APIs (Application Programming Interfaces), middleware, and networking solutions to enable smooth and reliable data flow.

SSH and Ethics

The Social Science & Humanities and ethics layer focuses on the responsible and ethical use of digital twin technology including social aspects. As digital twins gather extensive data, including potentially sensitive information, ethical considerations around data privacy, security, consent, and transparency become paramount. This layer addresses ethical concerns and ensures that the implementation of digital twins respects legal and societal norms, and safeguards data and privacy.

Face Blurring

A modular face anonymization system for ROS2