Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Week 01
Introduction
- What Makes a Robot smart?
Physical vs Virtual Robots
- Smart Robots, Smart Machines, Sentient Machines and Robotic Process Automation (RPA), etc.
The Role of Artificial Intelligence (AI) in Robotics
- Beyond "if-then-else" and the learning machine
- The algorithms behind AI
- Machine learning, computer vision, natural language processing (NLP), etc.
- Cognitive robotics
The Role of Big Data in Robotics
- Decision-making based on data and patterns
The Cloud and Robotics
- Linking robotics with IT
- Building more functional robots that access more information and collaborate
Case Study: Industrial Robots
-
Mechanical Robots
- Baxter
-
Robots in Nuclear Facilities
- Radiation detection and protection
-
Robots in Nuclear Reactors
- Radiation detection and protection
Hardware Components of a Robot
- Motors, sensors, microcontrollers, cameras, etc.
Common Elements of Robots
- Machine vision, voice recognition, speech synthesis, proximity sensing, pressure sensing, etc.
Development Frameworks for Programming a Robot
- Open source and commercial frameworks
-
Robot Operating System (ROS)
- Architecture: workspace, topics, messages, services, nodes, actionlibs, tools, etc.
Languages for Programming a Robot
- C++ for low level controlling
- Python for orchestration
- Programming ROS nodes in Python and C ++
- Other languages
Tools for Simulating a Physical Robot
- Commercial and open source 3D simulation and visualization software
Week 02
Preparing the Development Environment
- Software installation and setup
- Useful packages and utilities
Case Study: Mechanical Robots
- Robots in the nuclear technology field
- Robots in environmental systems
Programming the Robot
- Programming a node in Python and C ++
- Understanding ROS node
- Messages and topics in ROS
- Publication / subscription paradigm
- Project: Bump & Go with real robot
- Troubleshooting
- Simulation of robots with Gazebo / ROS
- Frames in ROS and reference changes
- 2D information processing of cameras with OpenCV
- Information processing of a laser
- Project: Safe tracking of objects by color
- Troubleshooting
Week 03
Programming the Robot (Continued...)
- Services in ROS
- 3D information processing of RGB-D sensors with PCL
- Maps and Navigation with ROS
- Project: Search for objects in the environment
- Troubleshooting
Programming the Robot (Continued...)
- ActionLib
- Speech Recognition and Speech Generation
- Controlling robotic arms with MoveIt!
- Controlling robotic neck for active vision
- Project: Search and collection of objects
- Troubleshooting
Testing Your Robot
- Unit testing
Week 04
Extending a Robot's Capabilities with Deep Learning
- Perception -- vision, audio, and haptics
- Knowledge representation
- Voice recognition through NLP (natural language processing)
- Computer vision
Crash Course in Deep Learning
- Artificial Neural Networks (ANNs)
- Artificial Neural Networks vs. Biological Neural Networks
- Feedforward Neural Networks
- Activation Functions
- Training Artificial Neural Networks
Crash Course in Deep Learning (Continued...)
- Deep Learning Models
- Convolutional Networks and Recurrent Networks
- Convolutional Neural Networks (CNNs or ConvNets)
- Convolution Layer
- Pooling Layer
- Convolutional Neural Networks Architecture
Week 05
Crash Course in Deep Learning (Continued...)
-
Recurrent Neural Networks (RNN)
- Training an RNN
- Stabilizing gradients during training
- Long short-term memory networks
-
Deep Learning Platforms and Software Libraries
- Deep Learning in ROS
Using Big Data in Your Robot
- Big data concepts
- Approaches to data analysis
- Big Data tooling
- Recognizing patterns in the data
- Exercise: NLP and Computer Vision on large data sets
Using Big Data in Your Robot (Continued...)
- Distributed processing of large data sets
- Coexistence and cross-fertilization of Big Data and Robotics
-
The robot as a generator of data
- Range measuring sensors, position, visual, tactile sensors, and other modalities
- Making sense of sensory data (sense-plan-act loop)
- Exercise: Capturing streaming data
Programming an Autonomous Deep Learning Robot
- Deep Learning robot components
- Setting up the robot simulator
- Running a CUDA-accelerated neural network with Cafe
- Troubleshooting
Week 06
Programming an Autonomous Deep Learning Robot (Continued...)
- Recognizing objects in photographs or video streams
- Enabling computer vision with OpenCV
- Troubleshooting
Data Analytics
- Using the robot to collect and organize new data
- Tools and processes for making sense of the data
Deploying a Robot
- Transitioning a simulated robot to physical hardware
- Deploying the robot in the physical world
- Monitoring and servicing robots in the field
Securing Your Robot
- Preventing unauthorized tampering
- Preventing hackers from viewing and stealing sensitive data
Building a Robot Collaboratively
- Building a robot in the cloud
- Joining the robotics community
Future Outlook for Robots in the Science and Energy Field
Summary and Conclusion
Requirements
- Programming experience in C or C++
- Programming experience in Python (useful but not necessary; can be taught as part of course)
- Experience with Linux command line
Audience
- Developers
- Engineers
- Scientists
- Technicians
120 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €11400 online delivery, based on a group of 2 delegates, €3600 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
Contact us for an exact quote and to hear our latest promotions
Public Training
Please see our public courses
Testimonials (1)
its knowledge and utilization of AI for Robotics in the Future.
