Robotics Training in Dartmouth

This instructor-led, live training in Dartmouth (online or onsite) is aimed at intermediate-level to advanced-level engineers and technicians who wish to learn how to program, operate, and optimize Fanuc and Epson robotic systems for industrial applications. By the end of this training, participants will be able to:

• Understand the architecture and functionalities of Fanuc and Epson robots.
• Program robot movements, logic, and sensor integrations.
• Implement safety protocols and troubleshooting techniques.
• Optimize robotic workflows for improved efficiency.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at intermediate-level participants who wish to explore the role of collaborative robots (cobots) and other human-centric AI systems in modern workplaces. By the end of this training, participants will be able to:

• Understand the principles of Human-Centric Physical AI and its applications.
• Explore the role of collaborative robots in enhancing workplace productivity.
• Identify and address challenges in human-machine interactions.
• Design workflows that optimize collaboration between humans and AI-driven systems.
• Promote a culture of innovation and adaptability in AI-integrated workplaces.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at beginner-level to intermediate-level marine engineers and technicians, and offshore operations personnel who wish to gain proficiency in operating and maintaining ROVs for underwater tasks. By the end of this training, participants will be able to:

• Understand the history, types, and applications of ROVs.
• Identify and explain the components and systems of an ROV.
• Navigate and communicate effectively with ROVs underwater.
• Pilot ROVs with precision in various underwater scenarios.
• Perform routine maintenance and troubleshoot common issues.
• Apply safety protocols during underwater operations.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at beginner-level robotics engineers who wish to thoroughly understand operating and programming the ABB IRB 2600ID robot for welding tasks. By the end of this training, participants will be able to:

• Understand how robotics is applied in welding.
• Develop proficiency in programming the ABB IRB 2600ID robot for various welding tasks.
• Learn to safely and effectively operate the ABB IRB 2600ID robot.
• Understand the safety standards and procedures relevant to robotic welding operations.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at advanced-level robotics engineers and AI researchers who wish to utilize Multimodal AI for integrating various sensory data to create more autonomous and efficient robots that can see, hear, and touch. By the end of this training, participants will be able to:

• Implement multimodal sensing in robotic systems.
• Develop AI algorithms for sensor fusion and decision-making.
• Create robots that can perform complex tasks in dynamic environments.
• Address challenges in real-time data processing and actuation.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at intermediate-level participants who wish to enhance their skills in designing, programming, and deploying intelligent robotic systems for automation and beyond. By the end of this training, participants will be able to:

• Understand the principles of Physical AI and its applications in robotics and automation.
• Design and program intelligent robotic systems for dynamic environments.
• Implement AI models for autonomous decision-making in robots.
• Leverage simulation tools for robotic testing and optimization.
• Address challenges such as sensor fusion, real-time processing, and energy efficiency.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at electrical engineers or anyone interested to have a more profound knowledge of semiconductors. By the end of this training, participants will be able to:

• Understand the concept of energy and conduction band diagrams.
• Understand the internal structure of diodes and how they work.
• Have an in-depth understanding of intrinsic and extrinsic semiconductors.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at beginner-level to intermediate-level participants who wish to learn how to use drones and photogrammetry techniques for infrastructure supervision in construction projects. By the end of this training, participants will be able to:

• Understand the fundamentals of drones and photogrammetry.
• Develop and execute drone flight plans for construction sites.
• Perform photogrammetry tracking and create detailed maps and 3D models.
• Use photogrammetry data for infrastructure supervision and issue detection.
• Apply drone technology to improve construction site safety and efficiency.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at beginner-level to intermediate-level and potentially advanced-level robotics developers who wish to learn how to use ROS to program mobile robots using Python. By the end of this training, participants will be able to:

• Set up a development environment that includes ROS, Python, and a mobile robot platform.
• Create and run ROS nodes, topics, services, and actions using Python.
• Use ROS tools and utilities to monitor and debug ROS applications.
• Use ROS packages and libraries to perform common tasks for mobile robots.
• Integrate ROS with other frameworks and tools.
• Troubleshooting and debugging ROS applications.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at electrical engineers or anyone interested to learn about the fundamentals of semiconductors and use to create different innovations in various fields. By the end of this training, participants will be able to:

• Know how electronic devices like diodes and transistors work.
• Analyze the carrier statistics in semiconductors.
• Understand the carrier dynamics of semiconductors and their resulting conduction properties.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at engineers and developers who wish to design, develop, and test aerial vehicles through exploring various aerial robotics concepts and tools. By the end of this training, participants will be able to:

• Understand the basics of aerial robotics.
• Model and design UAVs and quadrotors.
• Learn about the basics of flight control and motion planning.
• Learn how to use different simulation tools for aerial robotics.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at engineers who wish to program and create robots through basic AI methods. By the end of this training, participants will be able to:

• 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.

In this instructor-led, live training in Dartmouth (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 Dartmouth (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.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at developers and technical persons who wish to design and develop an unmanned drone. By the end of this training, participants will be able to:

• Setup a suitable development environment.
• Select and apply the right tools for programming a drone.
• Understand and configure the firmware, middleware and API stack.
• Test and debug their code using drone simulation software.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at developers who wish to install, configure, and manage AWS RoboMaker capabilities to create, simulate, and deploy applications for robots and autonomous vehicles and devices. By the end of this training, participants will be able to use AWS RoboMaker to build, simulate, deploy, manage, test, and monitor robot applications.

The Azure Bot Service combines the power of the Microsoft Bot Framework and Azure functions to enable rapid development of intelligent bots. In this instructor-led, live training, participants will learn how to easily create an intelligent bot using Microsoft Azure By the end of this training, participants will be able to:

• Learn the fundamentals of intelligent bots
• Learn how to create intelligent bots using cloud applications
• Understand how to use the Microsoft Bot Framework, the Bot Builder SDK, and the Azure Bot Service
• Understand how to design bots using bot patterns
• Develop their first intelligent bot using Microsoft Azure

Audience

• Developers
• Hobbyists
• Engineers
• IT Professionals

Format of the course

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

In this instructor-led, live training, participants will learn how to build a robot using Arduino hardware and the Arduino (C/C++) language. By the end of this training, participants will be able to:

• Build and operate a robotic system that includes both software and hardware components
• Understand the key concepts used in robotic technologies
• Assemble motors, sensors and microcontrollers into a working robot
• Design the mechanical structure of a robot

Audience

• Developers
• Engineers
• Hobbyists

Format of the course

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

Note

• Hardware kits will be specified by the instructor before the training, but will roughly contain the following components:

• Arduino board
• Motor controller
• Distance sensor
• Bluetooth slave
• Prototyping board and cables
• USB cable
• Vehicle kit

• Participants will need to purchase their own hardware.
• If you wish to customize this training, please contact us to arrange.

A bot or chatbot is like a computer assistant that is used to automate user interactions on various messaging platforms and get things done faster without the need for users to speak to another human. In this instructor-led, live training, participants will learn how to get started in developing a bot as they step through the creation of sample chatbots using bot development tools and frameworks. By the end of this training, participants will be able to:

• Understand the different uses and applications of bots
• Understand the complete process in developing bots
• Explore the different tools and platforms used in building bots
• Build a sample chatbot for Facebook Messenger
• Build a sample chatbot using Microsoft Bot Framework

Audience

• Developers interested in creating their own bot

Format of the course

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

This instructor-led, live training in Dartmouth (online or onsite) is aimed at anyone who wishes to understand the basics of UAS and apply drone technology in planning, operations, management, and analysis for various industries. By the end of this training, participants will be able to:

• Gain fundamental knowledge of UAVs and drones.
• Learn about drone classifications and uses to find suitable UAVs that address different needs.
• Evaluate delivery options and regulations for the convenient operation of drones.
• Understand the risks and ethics of using drone technology.
• Explore future uses and capabilities of UAVs including integration with other technologies.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at agriculture technicians, researchers, and engineers who wish to apply aerial robotics in optimizing data collection and analysis for agriculture. By the end of this training, participants will be able to:

• Understand drone technology and regulations related to it.
• Deploy drones to acquire, process, and analyze crop data to improve farming and agricultural methods.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at 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.

This course introduces machine learning methods in robotics applications. It is a broad overview of existing methods, motivations and main ideas in the context of pattern recognition. After a short theoretical background, participants will perform simple exercise using open source (usually R) or any other popular software.

This classroom based training session will explore NLP techniques in conjunction with the application of AI and Robotics in business. Delegates will undertake computer based examples and case study solving exercises using Python

This classroom based training session will explore Robotics and Robotic Process Automation (RPA). Delegates will undertake computer based examples and case study solving exercises.

In this instructor-led, live training in Dartmouth, participants will learn how to start using ROS for their robotics projects through the use of robotics visualization and simulation tools. By the end of this training, participants will be able to:

• Understand the basics of ROS.
• Learn how to create a basic robotics project using ROS.
• Learn how to use different tools for robotics including simulation and visualization tools.

ROS-Industrial (ROS-I) is an open-source project that builds on ROS. It extends the capabilities of ROS to manufacturing automation and robotics. In this instructor-led, live training, participants will learn how to start developing with ROS-Industrial. By the end of this training, participants will be able to:

• Install and configure ROS-Industrial
• Implement motion and path planning on ROS-I using tools such as MoveIt! and Descartes
• Create simple ROS-I applications
• Build, test, deploy, and troubleshoot a new robot with ROS-I

Audience

• Programmers
• Developers
• Engineers

Format of the course

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

Note

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

A Smart Robot is an Artificial Intelligence (AI) system that can learn from its environment and its experience and build on its capabilities based on that knowledge. Smart Robots can collaborate with humans, working along-side them and learning from their behavior. Furthermore, they have the capacity for not only manual labor, but cognitive tasks as well. In addition to physical robots, Smart Robots can also be purely software based, residing in a computer as a software application with no moving parts or physical interaction with the world. In this instructor-led, live training, participants will learn the different technologies, frameworks and techniques for programming different types of mechanical Smart Robots, then apply this knowledge to complete their own Smart Robot projects. The course is divided into 4 sections, each consisting of three days of lectures, discussions, and hands-on robot development in a live lab environment. Each section will conclude with a practical hands-on project to allow participants to practice and demonstrate 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 Smart Robots
• Build and operate a simulated mechanical Smart Robot that can see, sense, process, grasp, navigate, and interact with humans through voice
• Extend a Smart Robot's ability to perform complex tasks through Deep Learning
• Test and troubleshoot a Smart Robot in realistic scenarios

Audience

• Developers
• Engineers

Format of the course

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

Note

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

This instructor-led, live training in Dartmouth (online or onsite) is aimed at technical persons who wish to set up or extend an RPA system with more intelligent capabilities. By the end of this training, participants will be able to:

• Install and configure UiPath IPA.
• Enable robots to manage other robots.
• Apply computer vision to locate screen objects with accuracy.
• Enable robots that can detect language patterns and carry out sentiment analysis on unstructured content.