Physical AI with ROS 2: Self-Driving Robot in Python & C++. Master Localization, Mapping, SLAM & Particle Filter
Description
Would you like to build a real Self-Driving Robot using ROS2, the latest version of the Robot Operating System, by building a real robot?
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Would you like to dive into Physical AI and learn the theory and practice of Robot Localization, Mapping, and SLAM from industry experts?
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In this course, you will:
Learn the Probability Theory that makes robots robust to uncertainty
Understand Global Localization and the map, odom, and base_link frames
Use LiDAR and other sensors for localization and mapping
Compare Map Representations, from Occupancy Grids to topological maps
Build maps with known poses
Localize the robot in a known map with the Particle Filter (Monte Carlo Localization)
Implement SLAM (Simultaneous Localization and Mapping)
Simulate a Self-Driving Robot in Gazebo
The philosophy of this course is Learn by Doing, and quoting the American writer and teacher Dale Carnegie:
Learning is an Active Process. We learn by doing; only knowledge that is used sticks in your mind.
To help you master these concepts and use them in your projects and in your future job, I will guide you through every functionality of ROS 2, both from the theoretical and the practical point of view.
Each section is composed of three parts:
Theoretical explanation of the concept and functionality
Usage of the concept in a simple Practical example
Application of the functionality in a real Robot
There is more!
All the programming lessons are developed using both Python and C++. This means that you can choose the language you are most familiar with or become an expert Robotics Software Developer in both programming languages!
By taking this course, you will gain a deep understanding of self-driving robots, ROS 2, and the core skills behind Physical AI, opening up opportunities in the exciting field of robotics.
| Total Students | 6771 |
|---|---|
| Duration | 25 hours |
| Language | English (US) |
| Original Price | |
| Sale Price | 0 |
| Number of lectures | 160 |
| Number of quizzes | 2 |
| Total Reviews | 532 |
| Global Rating | 4.42 |
| Instructor Name | Antonio Brandi |
Course Insights (for Students)
Actionable, non-generic pointers before you enroll
Student Satisfaction
90% positive recent sentiment
Momentum
🔥 Trending
Time & Value
- Est. time: 25 hours
- Practical value: 8/10
Roadmap Fit
- Beginner → Intermediate → Advanced
Key Takeaways for Learners
- Hands-on practice
- Real-world examples
- Project-based learning
- Hands On
- Practical
Course Review Summary
Signals distilled from the latest Udemy reviews
What learners praise
- Hands On
- Practical
- Project
- Real World
- Well Structured
Watch-outs
- Theory only
- Missing project
Difficulty
Best suited for
Marketers with some platform experience, Doers who prefer project-led learning, Learners who like theory + frameworks
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