Multimodal AI in Robotics Training Course

Artificial Intelligence (AI) for Robotics merges machine learning, control systems, and sensor fusion to build intelligent machines that can perceive, reason, and act independently. By leveraging modern tools such as ROS 2, TensorFlow, and OpenCV, engineers are now able to design robots that navigate, plan, and interact with real-world environments intelligently.

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

Upon completing this training, participants will be able to:

• Utilize Python and ROS 2 to create 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.
• Use TensorFlow for motion prediction and learning-based control strategies.
• Integrate SLAM (Simultaneous Localization and Mapping) to enable autonomous navigation.
• Develop reinforcement learning models to enhance robotic decision-making capabilities.

Format of the Course

• Interactive lectures and discussions.
• Practical implementation using ROS 2 and Python.
• Hands-on exercises within simulated and real robotic environments.

Course Customization Options

To request a customized training session for this course, please get in touch with us to arrange your preferences.

In this instructor-led, live training in Brazil (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 6-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 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.
• 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 Brazil (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 (available online or onsite) targets intermediate-level robotics engineers and developers aiming to implement autonomous navigation and SLAM (Simultaneous Localization and Mapping) using ROS 2.

Upon completing 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 lectures and discussions.
• 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 customized training for this course, please contact us to arrange.

Azure Bot Service integrates the capabilities of the Microsoft Bot Framework and Azure Functions to offer a robust platform for rapidly constructing intelligent bots.

During this instructor-led live training, attendees will discover how to effectively develop intelligent bots using Microsoft Azure.

Upon completing the training, participants will be able to:

Comprehend the fundamental concepts underlying intelligent bots.

Construct intelligent bots leveraging cloud-based applications.

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

Implement established bot design patterns within real-world scenarios.

Develop and deploy their initial intelligent bot utilizing Microsoft Azure.

Audience

This course is tailored for developers, hobbyists, engineers, and IT professionals with an interest in bot development.

Course Format

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

OpenCV is an open-source computer vision library that enables real-time image processing, while deep learning frameworks such as TensorFlow provide the tools for intelligent perception and decision-making in robotic systems.

This instructor-led, live training (online or onsite) is aimed at intermediate-level robotics engineers, computer vision practitioners, and machine learning engineers who wish to apply computer vision and deep learning techniques for robotic perception and autonomy.

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

• Build computer vision pipelines using OpenCV.
• Incorporate deep learning models for object detection and recognition.
• Leverage vision-based data for robotic control and navigation.
• Blend classical vision algorithms with deep neural networks.
• Deploy computer vision systems on embedded and robotic platforms.

Format of the Course

• Interactive lecture and discussion.
• Hands-on practice using OpenCV and TensorFlow.
• Live-lab implementation on simulated or physical robotic systems.

Course Customization Options

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

A bot or chatbot functions as a digital assistant designed to automate user interactions across various messaging platforms, enabling faster task completion without requiring direct contact with a human agent.

In this instructor-led live training, participants will learn how to begin developing bots by creating sample chatbots using established bot development tools and frameworks.

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

• Identify the various uses and applications of bots
• Grasp the complete process involved in bot development
• Explore the diverse tools and platforms utilized for building bots
• Construct a sample chatbot for Facebook Messenger
• Build a sample chatbot using the Microsoft Bot Framework

Audience

• Developers interested in creating their own bots

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

Edge AI allows artificial intelligence models to execute directly on embedded or resource-limited devices, which reduces latency and power usage while enhancing autonomy and privacy within robotic systems.

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

Upon completing this training, participants will be capable of:

• Grasping the core principles of TinyML and edge AI for robotics.
• Converting and deploying AI models for on-device inference.
• Optimizing models to improve speed, reduce size, and increase energy efficiency.
• Integrating edge AI systems into robotic control architectures.
• Evaluating performance and accuracy in practical, real-world scenarios.

Course Format

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

Course Customization Options

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

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

Upon completing this training, participants will be equipped to:

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

Human-Robot Interaction (HRI): Voice, Gesture & Collaborative Control is a practical course aimed at introducing participants to the design and implementation of intuitive interfaces for human–robot communication. This training blends theoretical concepts, design principles, and programming practice to help participants create natural and responsive interaction systems using speech, gesture, and shared control techniques. Attendees will learn how to integrate perception modules, develop multimodal input systems, and design robots that safely collaborate with humans.

This instructor-led, live training (available online or onsite) is designed for 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.

Industrial Robotics Automation: ROS-PLC Integration & Digital Twins is a practical course designed to bridge the gap between industrial automation and modern robotics frameworks. Participants will learn how to integrate ROS-based robotic systems with PLCs for synchronized operations and explore digital twin environments to simulate, monitor, and optimize production processes. The course emphasizes interoperability, real-time control, and predictive analysis using digital replicas of physical systems.

This instructor-led, live training (available online or onsite) targets intermediate-level professionals who want to develop practical skills in connecting ROS-controlled robots with PLC environments and implementing digital twins for automation and manufacturing optimization.

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

• Understand the communication protocols between ROS and PLC systems.
• Implement real-time data exchange between robots and industrial controllers.
• Develop digital twins for monitoring, testing, and process simulation.
• Integrate sensors, actuators, and robotic manipulators within industrial workflows.
• Design and validate industrial automation systems using hybrid simulation environments.

Format of the Course

• Interactive lecture and architecture walkthroughs.
• Hands-on exercises integrating ROS and PLC systems.
• Simulation and digital twin project implementation.

Course Customization Options

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

This instructor-led live training in Brazil (online or onsite) is designed for engineers who wish to learn about the applicability of artificial intelligence to mechatronic systems.

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

• Gain an overview of artificial intelligence, machine learning, and computational intelligence.
• Understand the concepts of neural networks and different learning methods.
• Choose artificial intelligence approaches effectively for real-life problems.
• Implement AI applications in mechatronic engineering.

The Multi-Robot Systems and Swarm Intelligence advanced training course delves into the design, coordination, and control of robotic teams, drawing inspiration from biological swarm behaviors. Participants will acquire the skills to model interactions, implement distributed decision-making processes, and optimize collaboration across multiple agents. By blending theoretical foundations with practical simulation exercises, the course prepares learners for real-world applications in logistics, defense, search and rescue operations, and autonomous exploration.

This instructor-led training is available either online or onsite, catering to advanced professionals who aim to design, simulate, and deploy multi-robot and swarm-based systems utilizing open-source frameworks and algorithms.

Upon completing this training, participants will be capable of:

• Grasping the core principles and dynamics of swarm intelligence and cooperative robotics.
• Formulating communication and coordination strategies tailored for multi-robot systems.
• Deploying distributed decision-making mechanisms and consensus algorithms.
• Simulating collective behaviors including formation control, flocking dynamics, and area coverage.
• Applying swarm-based methodologies to practical scenarios and complex optimization challenges.

Course Format

• In-depth lectures featuring algorithmic analysis.
• Practical coding sessions and simulations using ROS 2 and Gazebo.
• A collaborative project focused on applying swarm intelligence principles.

Customization Options for the Course

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

An Intelligent Robot is an Artificial Intelligence (AI) system capable of learning from its environment and past experiences to enhance its capabilities based on that knowledge. These robots can collaborate with humans, working alongside them and observing their behavior. Beyond performing manual labor, they are also equipped for cognitive tasks. Intelligent Robots can be purely software-based, residing on a computer as an application without moving parts or physical interaction, in addition to being physical robots.

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

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

The hardware for this course is simulated in 3D using simulation software. Programming is conducted using the open-source ROS (Robot Operating System) framework, along with C++ and Python.

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

• Grasp the core concepts underlying robotic technologies.
• Understand and manage the interaction between software and hardware in a robotic system.
• Understand and implement the software components that form the foundation of Intelligent Robots.
• Build and operate a simulated mechanical Intelligent Robot capable of seeing, sensing, processing, grasping, navigating, and interacting with humans via voice.
• Enhance an Intelligent Robot's ability to perform complex tasks through Deep Learning.
• Test and troubleshoot an Intelligent Robot in realistic scenarios.

Target Audience

• Developers
• Engineers

Course Format

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

Note

• To customize any aspect of this course (e.g., programming language, robot model), please contact us to arrange.

Intelligent robotics involves embedding artificial intelligence into robotic systems to enhance perception, decision-making capabilities, and autonomous control.

This instructor-led training (available online or on-site) is designed for advanced robotics engineers, systems integrators, and automation leads who want to implement AI-driven perception, planning, and control within smart manufacturing environments.

Upon completing this training, participants will be able to:

• Comprehend and apply AI techniques for robotic perception and sensor fusion.
• Create motion planning algorithms for both collaborative and industrial robots.
• Implement learning-based control strategies to enable real-time decision-making.
• Integrate intelligent robotic systems into smart factory workflows.

Course Format

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

Customization Options

• For a customized training session, please contact us to make arrangements.