Industrial Robotics Automation: ROS-PLC Integration & Digital Twins Training Course

Artificial Intelligence (AI) for Robotics merges machine learning, control systems, and sensor fusion to build intelligent machines capable of perceiving, reasoning, and acting autonomously. Leveraging modern tools such as ROS 2, TensorFlow, and OpenCV, engineers can design robots that navigate, plan, and interact with real-world environments with sophistication.

This instructor-led, live training (available online or onsite) is tailored for intermediate-level engineers looking to develop, train, and deploy AI-driven robotic systems using contemporary open-source technologies and frameworks.

Upon completion of this training, participants will be able to:

• Utilize Python and ROS 2 to construct and simulate robotic behaviors.
• Implement Kalman and Particle Filters for localization and tracking purposes.
• Apply computer vision techniques via OpenCV for perception and object detection.
• Employ TensorFlow for motion prediction and learning-based control.
• Integrate SLAM (Simultaneous Localization and Mapping) to enable autonomous navigation.
• Develop reinforcement learning models to enhance robotic decision-making.

Format of the Course

• Interactive lecture and discussion.
• Hands-on implementation using ROS 2 and Python.
• Practical exercises involving simulated and real robotic environments.

Course Customization Options

To request a customized training for this course, please contact us to arrange.

This instructor-led live training, conducted Italy (online or onsite), allows participants to learn the diverse technologies, frameworks, and techniques for programming various robots applicable to nuclear technology and environmental systems.

The six-week course meets five days a week. Each day involves four hours of lectures, discussions, and hands-on robot development in a live lab environment. Participants will engage in real-world projects relevant to their work to practice their acquired knowledge.

The target hardware for this course is simulated in 3D via simulation software. The ROS (Robot Operating System) open-source framework, C++, and Python are employed for programming the robots.

By the end of this training, participants will be able to:

• Understand the key concepts used in robotic technologies.
• Understand and manage the interaction between software and hardware in a robotic system.
• Understand and implement the software components that underpin robotics.
• Build and operate a simulated mechanical robot that can see, sense, process, navigate, and interact with humans through voice.
• Understand the necessary elements of artificial intelligence (machine learning, deep learning, etc.) applicable to building a smart robot.
• Implement filters (Kalman and Particle) to enable the robot to locate moving objects in its environment.
• Implement search algorithms and motion planning.
• Implement PID controls to regulate a robot's movement within an environment.
• Implement SLAM algorithms to enable a robot to map out an unknown environment.
• Extend a robot's ability to perform complex tasks through Deep Learning.
• Test and troubleshoot a robot in realistic scenarios.

In this instructor-led live training in Italy (online or onsite), participants will learn the different technologies, frameworks and techniques for programming different types of robots to be used in the field of nuclear technology and environmental systems.

The 4-week course is held 5 days a week. Each day is 4-hours long and consists of lectures, discussions, and hands-on robot development in a live lab environment. Participants will complete various real-world projects applicable to their work in order to practice their acquired knowledge.

The target hardware for this course will be simulated in 3D through simulation software. The code will then be loaded onto physical hardware (Arduino or other) for final deployment testing. The ROS (Robot Operating System) open-source framework, C++ and Python will be used for programming the robots.

By the end of this training, participants will be able to:

• Understand the key concepts used in robotic technologies.
• Understand and manage the interaction between software and hardware in a robotic system.
• Understand and implement the software components that underpin robotics.
• Build and operate a simulated mechanical robot that can see, sense, process, navigate, and interact with humans through voice.
• Understand the necessary elements of artificial intelligence (machine learning, deep learning, etc.) applicable to building a smart robot.
• Implement filters (Kalman and Particle) to enable the robot to locate moving objects in its environment.
• Implement search algorithms and motion planning.
• Implement PID controls to regulate a robot's movement within an environment.
• Implement SLAM algorithms to enable a robot to map out an unknown environment.
• Test and troubleshoot a robot in realistic scenarios.

ROS 2 (Robot Operating System 2) is an open-source framework designed to support the development of complex and scalable robotic applications.

This instructor-led, live training (online or onsite) is aimed at intermediate-level robotics engineers and developers who wish to implement autonomous navigation and SLAM (Simultaneous Localization and Mapping) using ROS 2.

By the end of this training, participants will be able to:

• Set up and configure ROS 2 for autonomous navigation applications.
• Implement SLAM algorithms for mapping and localization.
• Integrate sensors such as LiDAR and cameras with ROS 2.
• Simulate and test autonomous navigation in Gazebo.
• Deploy navigation stacks on physical robots.

Format of the Course

• Interactive lecture and discussion.
• Hands-on practice using ROS 2 tools and simulation environments.
• Live-lab implementation and testing on virtual or physical robots.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Azure Bot Service integrates the functionalities of the Microsoft Bot Framework and Azure Functions, offering a robust platform for rapidly constructing intelligent bots.

Through this instructor-led live training, attendees will learn how to efficiently create intelligent bots using Microsoft Azure.

Upon completion of the training, participants will be capable of:

Grasping the fundamental concepts underlying intelligent bots.

Constructing intelligent bots leveraging cloud-based applications.

Acquiring practical expertise in the Microsoft Bot Framework, the Bot Builder SDK, and Azure Bot Service.

Implementing established bot design patterns in practical scenarios.

Creating and deploying their initial intelligent bot via Microsoft Azure.

Target Audience

This course is tailored for developers, enthusiasts, engineers, and IT professionals keen on bot development.

Course Format

The training merges lectures and discussions with exercises, placing a strong emphasis on hands-on practice.

OpenCV serves as an open-source computer vision library that facilitates real-time image processing, while deep learning frameworks like TensorFlow equip robotic systems with the capabilities needed for intelligent perception and decision-making.

This instructor-led live training, available online or onsite, is designed for intermediate-level robotics engineers, computer vision specialists, and machine learning professionals who want to leverage computer vision and deep learning techniques to enhance robotic perception and autonomy.

Upon completing this training, participants will be able to:

• Build computer vision pipelines using OpenCV.
• Integrate deep learning models for the detection and recognition of objects.
• Leverage vision-based data for controlling and navigating robots.
• Blend classical vision algorithms with deep neural networks.
• Deploy computer vision solutions on embedded and robotic platforms.

Course Format

• Interactive lectures and discussions.
• Practical exercises using OpenCV and TensorFlow.
• Live laboratory implementation on simulated or physical robotic systems.

Customization Options

• To arrange a customized training session for this course, please reach out to us.

A bot, or chatbot, acts as a virtual assistant designed to automate user interactions across various messaging platforms, enabling tasks to be completed more efficiently without requiring direct human intervention.

In this instructor-led live training, participants will learn the fundamentals of bot development by creating sample chatbots using dedicated development tools and frameworks.

By the conclusion of this training, participants will be able to:

• Grasp the diverse use cases and applications of bots
• Comprehend the end-to-end bot development lifecycle
• Investigate the various tools and platforms utilized in bot construction
• Construct a sample chatbot for Facebook Messenger
• Develop a sample chatbot using the Microsoft Bot Framework

Audience

• Developers interested in creating their own bots

Course Format

• A blend of lectures, discussions, exercises, and extensive hands-on practice

Edge AI allows artificial intelligence models to operate directly on embedded or resource-constrained devices, thereby lowering latency and power usage while boosting autonomy and privacy within robotic systems.

This instructor-led live training, available online or on-site, targets intermediate-level embedded developers and robotics engineers looking to implement machine learning inference and optimization techniques directly on robotic hardware via TinyML and edge AI frameworks.

Upon completing this training, participants will be able to:

• Grasp the core principles of TinyML and edge AI for robotics.
• Convert and deploy AI models for on-device inference.
• Optimize models to improve speed, reduce size, and enhance energy efficiency.
• Integrate edge AI systems into robotic control architectures.
• Assess performance and accuracy in real-world applications.

Course Format

• Interactive lectures and discussions.
• Practical exercises utilizing TinyML and edge AI toolchains.
• Hands-on work with embedded and robotic hardware platforms.

Customization Options

• To arrange a tailored training session for this course, please contact us.

This instructor-led, live training in Italy (online or onsite) is designed for intermediate-level participants interested in exploring the role of collaborative robots (cobots) and other human-centric AI systems in modern workplaces.

Upon completion of this training, participants will be equipped to:

• Grasp the core principles of Human-Centric Physical AI and their practical applications.
• Examine how collaborative robots contribute to enhancing workplace efficiency.
• Recognize and resolve challenges associated with human-machine interactions.
• Develop workflows that maximize collaboration between humans and AI-driven systems.
• Foster a workplace culture rooted in innovation and adaptability within AI-integrated environments.

Human-Robot Interaction (HRI): Voice, Gesture & Collaborative Control is a practical course designed to introduce participants to the design and implementation of intuitive interfaces for human–robot communication. The training combines theory, design principles, and programming practice to build natural and responsive interaction systems using speech, gesture, and shared control techniques. Participants will learn how to integrate perception modules, develop multimodal input systems, and design robots that safely collaborate with humans.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level participants who wish to design and implement human–robot interaction systems that enhance usability, safety, and user experience.

By the end of this training, participants will be able to:

• Understand the foundations and design principles of human–robot interaction.
• Develop voice-based control and response mechanisms for robots.
• Implement gesture recognition using computer vision techniques.
• Design collaborative control systems for safe and shared autonomy.
• Evaluate HRI systems based on usability, safety, and human factors.

Format of the Course

• Interactive lectures and demonstrations.
• Hands-on coding and design exercises.
• Practical experiments in simulation or real robotic environments.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Italy (online or onsite) is aimed at intermediate-level automation engineers and control system designers who wish to implement motion control solutions using Omron PLCs.

By the end of this training, participants will be able to:

• Understand fundamental motion control concepts and their applications.
• Configure motion hardware and software in Sysmac Studio.
• Program and optimize single-axis and multi-axis motion control.
• Implement coordinated motion strategies, including interpolation and synchronization.

This instructor-led, live training in Italy (online or onsite) is aimed at intermediate-level programmers who wish to enhance their skills in Omron PLC programming, HMI configuration, motion control, and safety systems.

By the end of this training, participants will be able to:

• Configure and program Omron PLCs using Sysmac Studio.
• Understand and apply IEC concepts in ladder logic and structured text programming.
• Develop motion control programs for single-axis and coordinated movements.
• Create HMI interfaces using the NA series and integrate them with Sysmac controllers.
• Implement and simulate safety standards and programs using NX series safety hardware.

This course provides an introduction to the fundamentals of Programmable Logic Controllers (PLC). Following an overview of key PLC concepts, participants will learn and practice essential Ladder Diagram instructions through practical Industrial Automation exercises. Target audience: Electrical Specialists, Mechanical Engineers, and Programmers with an interest in Industrial Automation.

A Smart Robot is an Artificial Intelligence (AI) system capable of learning from its surroundings and experiences, thereby enhancing its capabilities based on acquired knowledge. These robots can collaborate with humans, working alongside them and learning from their behavior. Beyond physical tasks, Smart Robots are also equipped to handle cognitive duties. While some are mechanical, Smart Robots can also exist as purely software-based applications within a computer, operating without moving parts or direct physical interaction with the world.

In this instructor-led live training, participants will explore the various technologies, frameworks, and techniques used to program different types of mechanical Smart Robots, applying this knowledge to develop their own Smart Robot projects.

The course is structured into 4 sections, each comprising three days of lectures, discussions, and hands-on robot development in a live lab. Each section concludes with a practical project, allowing participants to practice and demonstrate their acquired skills.

The course hardware is simulated in 3D using simulation software. The open-source ROS (Robot Operating System) framework, along with C++ and Python, will be utilized for robot programming.

Upon completion of this training, participants will be able to:

• Grasp the fundamental concepts of robotic technologies
• Manage the interaction between software and hardware in robotic systems
• Understand and implement the software components that support Smart Robots
• Build and operate a simulated mechanical Smart Robot capable of seeing, sensing, processing, grasping, navigating, and interacting with humans via voice
• Enhance a Smart Robot's ability to perform complex tasks using Deep Learning
• Test and troubleshoot Smart Robots in realistic scenarios

Audience

• Developers
• Engineers

Course Format

• Blend of lectures, discussions, exercises, and extensive hands-on practice

Note

• To customize any aspect of this course (programming language, robot model, etc.), please contact us to make arrangements.

Smart Robotics involves integrating artificial intelligence into robotic systems to enhance perception, decision-making capabilities, and autonomous control.

This instructor-led live training, available either online or on-site, is designed for advanced robotics engineers, systems integrators, and automation leaders who aim to implement AI-driven perception, planning, and control within smart manufacturing settings.

Upon completing this training, participants will be capable of:

• Understanding and applying AI techniques for robotic perception and sensor fusion.
• Developing motion planning algorithms for both collaborative and industrial robots.
• Deploying learning-based control strategies to facilitate real-time decision making.
• Integrating intelligent robotic systems into smart factory workflows.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical practice sessions.
• Hands-on implementation within a live-lab environment.

Course Customization Options

• To request customized training for this course, please reach out to us to arrange the details.