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Robot Operating System (ROS)

Master ROS to develop, simulate, control, and deploy intelligent robotic systems using modern robotics middleware, sensors, navigation, and autonomous
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Course Duration: 10 Hours
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Robotics is rapidly transforming industries ranging from manufacturing and healthcare to logistics, agriculture, space exploration, and autonomous transportation. At the core of this transformation lies a powerful and widely adopted middleware framework known as the Robot Operating System (ROS). ROS has become the de-facto standard software platform for building intelligent robotic systems, enabling developers to design complex robot behaviors by integrating perception, planning, control, and communication modules in a scalable and reusable way.
 
Despite its name, ROS is not an operating system in the traditional sense. Instead, it is a flexible robotics software framework that provides tools, libraries, communication protocols, and conventions to simplify the development of robotic applications. ROS allows engineers to focus on solving high-level robotics problems rather than reinventing low-level communication, hardware abstraction, and data-exchange mechanisms.
 
The ROS course by Uplatz provides a comprehensive, hands-on journey into robotics software engineering using ROS. This course is designed for learners who want to build real robotic systems — from mobile robots and robotic arms to autonomous vehicles and drones. You will learn how ROS enables modular, distributed systems where multiple processes (called nodes) communicate seamlessly using publish-subscribe and service-based architectures.
 
The course begins with foundational robotics and ROS concepts, ensuring that learners understand how ROS fits into the broader robotics ecosystem. You will explore ROS architecture, including nodes, topics, messages, services, actions, parameters, and launch files. These components form the backbone of every ROS-based robot and enable scalable, fault-tolerant system design.
 
A major emphasis of this course is hands-on robotics development. You will learn how to write ROS nodes in Python and C++, interface with sensors such as LiDAR, cameras, IMUs, and encoders, and control actuators like motors and robotic arms. The course also covers simulation using Gazebo and RViz, allowing learners to design and test robots in virtual environments before deploying them on real hardware.
 
As robotics systems grow in complexity, managing concurrency, real-time data flow, and distributed computation becomes critical. ROS excels in this area by providing standardized communication tools that allow multiple subsystems — perception, localization, navigation, and manipulation — to operate independently yet cohesively. You will learn how to design such systems and debug them using ROS command-line tools and visualization utilities.
 
The course also dives into robot perception and autonomy. You will learn how robots perceive their environment using sensor fusion, computer vision, and point-cloud processing. Topics such as mapping (SLAM), localization, path planning, and obstacle avoidance are introduced using ROS navigation stacks. These skills are essential for building autonomous robots capable of operating in dynamic environments.
 
Another key focus is ROS in real-world deployments. You will learn how ROS is used in industry to power autonomous warehouses, robotic manufacturing lines, delivery robots, agricultural robots, and research platforms. The course covers best practices for deploying ROS on embedded systems, single-board computers, and industrial controllers, as well as integrating ROS with cloud services and AI pipelines.
 
The course also addresses the evolution of ROS into ROS 2, which introduces improved real-time performance, enhanced security, better support for embedded systems, and modern middleware standards (DDS). You will understand the differences between ROS 1 and ROS 2, and how to migrate or choose between them depending on your application.
 
By the end of this course, learners will have the skills to design, simulate, and deploy complete robotic systems using ROS — from concept to production.
🔍 What Is ROS?
 
The Robot Operating System (ROS) is an open-source robotics middleware framework that provides:

  • Hardware abstraction

  • Inter-process communication

  • Device drivers

  • Message passing

  • Package management

  • Simulation and visualization tools

ROS allows robots to be built as collections of independent software components that communicate efficiently, enabling scalable and reusable system design.
⚙️ How ROS Works
 
ROS operates using a modular, distributed architecture:
 
1. Nodes
 
Independent processes that perform specific tasks (e.g., sensor reading, motor control).
 
2. Topics & Messages
 
Publish-subscribe communication for streaming data such as sensor readings.
 
3. Services & Actions
 
Request-response and long-running task execution mechanisms.
 
4. Parameters & Configuration
 
Centralized configuration for system behavior.
 
5. Launch Files
 
Tools to start and manage multiple nodes together.
 
6. Simulation & Visualization
 
Integration with Gazebo and RViz for testing and debugging.
🏭 Where ROS Is Used in the Industry
 
ROS is widely used across robotics domains:
 
1. Manufacturing & Industrial Automation
 
Robotic arms, assembly lines, quality inspection.
 
2. Autonomous Vehicles & Drones
 
Navigation, perception, and control systems.
 
3. Logistics & Warehousing
 
Autonomous mobile robots for inventory and delivery.
 
4. Healthcare & Medical Robotics
 
Surgical robots, rehabilitation devices, assistive robots.
 
5. Agriculture
 
Autonomous tractors, crop monitoring robots.
 
6. Research & Education
 
Academic robotics research and prototyping.
 
7. Space & Exploration
 
Planetary rovers and robotic exploration systems.
🌟 Benefits of Learning ROS
 
By learning ROS, you gain:

  • Industry-standard robotics development skills

  • Ability to build scalable robotic software

  • Hands-on experience with real robot systems

  • Expertise in simulation-based development

  • Strong foundation for autonomous robotics

  • Skills transferable across multiple robot platforms

  • High employability in robotics and automation roles

📘 What You’ll Learn in This Course
 
You will explore:

  • ROS architecture and core concepts

  • Writing ROS nodes in Python and C++

  • Interfacing with sensors and actuators

  • Robot simulation using Gazebo

  • Visualization using RViz

  • Navigation, mapping, and localization

  • Robot control and motion planning

  • ROS debugging and performance tuning

  • ROS 2 fundamentals and differences

  • Building a complete autonomous robot system

🧠 How to Use This Course Effectively

  • Start with ROS basics and command-line tools

  • Build simple publisher-subscriber examples

  • Move to sensor integration and control

  • Practice in simulation before hardware deployment

  • Experiment with navigation and autonomy stacks

  • Complete the capstone project step by step

👩‍💻 Who Should Take This Course

  • Robotics Engineers

  • Mechatronics Engineers

  • Automation Engineers

  • Embedded Systems Developers

  • AI & Computer Vision Engineers

  • Students in robotics, electronics, or AI

  • Researchers building robotic platforms

Basic Python or C++ knowledge is helpful.
🚀 Final Takeaway
 
ROS is the backbone of modern robotics development. Mastering ROS empowers you to build intelligent, autonomous, and scalable robotic systems used across industries worldwide. This course equips you with both the theoretical understanding and hands-on skills needed to succeed in robotics engineering.

Course Objectives Back to Top

By the end of this course, learners will:

  • Understand ROS architecture and communication

  • Develop ROS nodes using Python and C++

  • Integrate sensors and actuators

  • Simulate robots using Gazebo

  • Visualize and debug systems using RViz

  • Implement navigation and autonomy features

  • Work with ROS 2 fundamentals

  • Build and deploy a complete robotic system

Course Syllabus Back to Top

Course Syllabus

Module 1: Introduction to Robotics & ROS

  • Robotics overview

  • Why ROS?

Module 2: ROS Architecture & Concepts

  • Nodes, topics, services, actions

Module 3: ROS Development Environment

  • Installation

  • Workspace setup

Module 4: Writing ROS Nodes

  • Python & C++ nodes

Module 5: Communication in ROS

  • Topics, messages, services

Module 6: Sensors & Actuators

  • Cameras, LiDAR, motors

Module 7: Simulation with Gazebo

  • Robot models

  • Physics simulation

Module 8: Visualization with RViz

  • Sensor data visualization

  • Debugging

Module 9: Navigation & SLAM

  • Mapping

  • Localization

  • Path planning

Module 10: ROS 2 Fundamentals

  • DDS

  • Real-time communication

Module 11: Deployment & Best Practices

  • Embedded systems

  • Performance optimization

Module 12: Capstone Project

  • Build an autonomous mobile robot

Certification Back to Top

Learners receive a Uplatz Certificate in Robot Operating System (ROS), validating practical skills in robotics software development, simulation, and deployment.

Career & Jobs Back to Top

This course prepares learners for roles such as:

  • Robotics Engineer

  • Autonomous Systems Engineer

  • Mechatronics Engineer

  • Embedded Robotics Developer

  • Automation Engineer

  • Research Engineer (Robotics)

Interview Questions Back to Top

1. What is ROS?

A robotics middleware framework for building distributed robotic systems.

2. Is ROS an operating system?

No — it is a software framework running on top of an OS.

3. What is a ROS node?

A process that performs a specific task in a robotic system.

4. What are ROS topics?

Publish-subscribe channels for streaming data.

5. What is Gazebo used for?

Robot simulation and physics-based testing.

6. What is RViz?

A visualization tool for robot data and debugging.

7. What is SLAM?

Simultaneous Localization and Mapping.

8. What is ROS 2?

The next-generation ROS with real-time and security improvements.

9. Which languages does ROS support?

Primarily Python and C++.

10. Where is ROS used?

In autonomous robots, drones, industrial automation, and research.

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