ROS Developer
Unlock the world of robotics with our comprehensive ROS course, where you’ll learn to design and implement advanced robotic systems using ROS and integrate machine learning for autonomous behavior. Gain hands-on experience in navigation, localization, and manipulation, preparing you for real-world applications in the rapidly evolving field of robotics.
Course Program
What you'll learn
- Advanced concepts of the Robot Operating System (ROS) and its applications in robotics.
- Techniques for robot navigation, localization, mapping, and manipulation.
- Integration of machine learning with ROS for autonomous behaviors.
Course Program
Requirements
- Basic programming skills in Python or C++.
- Familiarity with robotics concepts and principles.
- Prior experience with Linux operating systems.
- Beginner Class: For students new to programming or with no prior experience.
- Advance Class: For students with programming basics or who have completed the beginner level.
Course content
Beginner class
Advance class
Beginner class
- Introduction to ROS (Robot Operating System)
Overview of ROS, its architecture, history, and use cases in robotics development. - Setting Up ROS Development Environment
Installing ROS (Noetic or ROS2), setting up Ubuntu, and configuring workspaces. - ROS Basics: Nodes, Topics, and Messages
Understanding the core concepts of ROS such as nodes, topics, and messages for inter-process communication. - Creating and Running ROS Nodes
Writing and running simple ROS nodes using Python (rospy) and C++ (roscpp). - Understanding ROS Launch Files
Creating and using launch files to start multiple nodes simultaneously. - ROS Parameters and Parameter Server
Managing parameters using the ROS parameter server for node configuration. - Working with ROS Publishers and Subscribers
Setting up publisher-subscriber communication between nodes using topics. - Introduction to ROS Services and Actions
Understanding services and actions for request-response and goal-based interactions between nodes. - Interfacing with Sensors: LIDAR, Cameras, and IMUs
Connecting sensors like LIDAR, cameras, and IMUs to ROS and processing sensor data. - ROS TF: Working with Coordinate Frames
Using the ROS TF library to manage coordinate transformations between different parts of the robot. - Simulating Robots with Gazebo and RViz
Running robot simulations using Gazebo and visualizing robot models and sensor data in RViz. - Working with URDF for Robot Modeling
Creating and understanding URDF files to model robots in ROS and visualize them in RViz. - Building a Simple Mobile Robot in ROS
A project where students design and control a simple mobile robot using ROS and sensors. - Controlling Robots: Teleoperation and Joystick Control
Implementing teleoperation of a robot using keyboard input or a joystick. - ROS Packages: Structure and Best Practices
Organizing ROS projects into packages and learning best practices for creating reusable packages. - Deploying a Simple ROS Project
Final project: Building, simulating, and controlling a robot using ROS nodes, topics, and sensors.
Advance class
- Advanced ROS Architecture: ROS2 and DDS Communication
Introduction to ROS2, exploring differences from ROS1, and understanding DDS (Data Distribution Service). - Working with ActionLib in ROS
Implementing action servers and clients for long-running tasks such as robot navigation and control. - Path Planning and Navigation in ROS
Using the ROS Navigation stack for 2D/3D path planning and controlling robot movement in dynamic environments. - SLAM (Simultaneous Localization and Mapping) in ROS
Implementing SLAM algorithms (gmapping, Hector SLAM) for real-time map building and robot localization. - ROS Control: Actuators and Robot Manipulation
Using ROS control for robotic arms and manipulators, working with controllers, and configuring joints. - Robot Localization and Sensor Fusion with ROS
Implementing sensor fusion algorithms like EKF (Extended Kalman Filter) for accurate robot localization using multiple sensors. - Object Detection and Tracking with Computer Vision in ROS
Integrating OpenCV and YOLO for object detection and tracking in a ROS environment. - Robotic Arm Manipulation: MoveIt! with ROS
Using the MoveIt! framework for controlling robotic arms, motion planning, and trajectory execution. - Building Autonomous Robots: Integration of Perception and Navigation
Combining perception, localization, and navigation for building fully autonomous mobile robots. - Multi-Robot Systems in ROS
Implementing multi-robot coordination, communication, and task allocation in ROS environments. - Advanced Simulation Techniques with Gazebo
Creating advanced simulations in Gazebo, incorporating complex physics, and adding custom sensors and actuators. - Advanced ROS TF: Dynamic Coordinate Frames and Kinematics
Working with dynamic TF frames and performing forward and inverse kinematics calculations in ROS. - ROS and Machine Learning: Autonomous Behavior
Integrating machine learning algorithms with ROS for tasks like autonomous navigation and decision-making. - Robot Hardware Interfacing and Real-World Deployment
Connecting ROS to real robot hardware, interfacing with motor drivers, sensors, and deploying ROS on embedded systems. - ROS Security and Best Practices for Deployment
Securing ROS communication, managing network resources, and best practices for deploying ROS in production environments.
Course Program
Capstone Project
Autonomous Line-Following Robot: Create a robot that uses sensors to detect and follow a line, implementing basic navigation and control techniques.
Simple Object Tracker: Develop a robot that utilizes a camera and computer vision to detect and track a moving object in its environment.
SLAM Mapping Demo: Build a robot that explores an area and generates a map in real-time using SLAM algorithms, demonstrating localization and mapping capabilities.
Robotic Arm Task Automation: Design a robotic arm that can perform simple pick-and-place tasks using ROS control and MoveIt! for motion planning.
Multi-Robot Coordination Simulation: Implement a simulation with multiple robots collaborating to complete a shared task in Gazebo, showcasing communication and task allocation.
Course Program
Outcomes
- Ability to design, develop, and deploy autonomous robotic systems.
- Proficiency in implementing advanced ROS features for navigation and control.
- Competence in integrating various sensors and actuators for real-world applications.