Robotics Tutorials
Modelling in ROS, AI and Machine Learning
From ROS 2 fundamentals to deep learning and autonomous navigation — building intelligent robotic systems
9 chapters · 18 credit hours
- Ch. 01Read →
Introduction to ROS & ROS 2
Robot Operating System Architecture and Ecosystem
2 hours
- Ch. 02Read →
Core Concepts of ROS
Nodes, Topics, Services, Actions and the ROS Graph
2 hours
- Ch. 03Read →
Machine Learning in Robotics: Software Architecture & Behavior-Based Systems
AI Integration Patterns and Reactive Robot Architectures
2 hours
- Ch. 04Read →
Core Concepts of ROS (Continued)
TF2, Launch Files, Parameters, and ROS Tooling
2 hours
- Ch. 05Read →
Neural Networks and Genetic Algorithms in Robotics
Evolutionary and Learning-Based Control Methods
2 hours
- Ch. 06Read →
Implementation of Core Concepts in ROS
Hands-On ROS Programming: Publishers, Subscribers, and Services
2 hours
- Ch. 07Read →
Introduction to Deep Learning and Applications in Robotics
CNNs, Transformers, and Reinforcement Learning for Robots
2 hours
- Ch. 08Read →
CAD Design and Simulation in ROS
URDF, Gazebo, and Robot Modelling Workflows
2 hours
- Ch. 09Read →
Localisation and Navigation in ROS
SLAM, Costmaps, and the Navigation Stack
2 hours