Welcome to RealSense University - your comprehensive online curriculum for mastering RealSense 3D stereo cameras from beginner to expert level.
RealSense University is designed to take you from complete beginner to expert developer in working with RealSense cameras. Whether you're building robotics applications, computer vision systems, or AI-powered solutions, this curriculum provides structured learning with hands-on projects.
Goal: Understand what RealSense is, install it, and capture your first 3D data.
- Module 1: Introduction to RealSense Cameras
- Module 2: Setup & Installation
- Module 3: Depth & Color Basics
- Module 4: Your First Python Script
- Module 5: Mini Project - Distance Measurement
Goal: Learn to integrate RealSense with robotics frameworks and computer vision tools.
- Module 1: Working with Point Clouds
- Module 2: Using RealSense in ROS2
- Module 3: Depth-Based Applications
- Module 4: Cross-Platform Development
- Module 5: Mini Project - Obstacle Detection
Goal: Integrate RealSense depth perception with AI, SLAM, and embodied robotics.
- Module 1: Visual SLAM & Mapping
- Module 2: Sensor Fusion
- Module 3: AI Perception Pipelines
- Module 4: Remote and Cloud Robotics
- Module 5: Mini Project - Autonomous Navigation
Goal: Enable power users to innovate with RealSense and contribute to the ecosystem.
- Track 1: RealSense for Humanoids
- Track 2: RealSense + OpenVINO Mastery
- Track 3: RealSense Developer SDK Extensions
- Track 4: Capstone Project
- Video Series
- Documentation & Resources
- Code Examples & Templates
- Community & Support
- Certification Program
- New to RealSense? Start with Level 1: Beginner
- Have some experience? Jump to Level 2: Intermediate
- Ready for advanced topics? Explore Level 3: Advanced
- Want to become an expert? Master Level 4: Expert
- Basic programming knowledge (Python recommended)
- Computer with USB 3.0 port
- RealSense camera (D405, D415, D435, D455, D457, or D555)
- Completion of Level 1 or equivalent experience
- Basic understanding of robotics concepts
- Linux environment (Ubuntu 20.04+ recommended)
- Completion of Level 2 or equivalent experience
- Familiarity with ROS2
- Understanding of computer vision and AI concepts
- Completion of Level 3 or equivalent experience
- Advanced programming skills
- Experience with embedded systems and optimization
| Level | Minimum Requirements | Recommended |
|---|---|---|
| Level 1 | RealSense D415/D435, USB 3.0, 8GB RAM | RealSense D455, 16GB RAM |
| Level 2 | Level 1 + Linux system | NVIDIA GPU, ROS2 compatible hardware |
| Level 3 | Level 2 + IMU-enabled camera | Multi-camera setup, high-end GPU |
| Level 4 | Level 3 + development board | Custom hardware, multiple sensors |
Level 1 → Level 2 → Level 3 (Modules 1-2) → Level 4 (Track 1)
Level 1 → Level 2 (Modules 1,3) → Level 3 (Modules 3-4) → Level 4 (Track 2)
Level 1 → Level 2 (Module 4) → Level 3 (Module 2) → Level 4 (Track 3)
We welcome contributions to RealSense University! Please see our Contributing Guidelines for details.
This curriculum is licensed under the MIT License.
- 📧 Email: [email protected]
- 💬 Discord: Join our community
- 📚 Documentation: Official RealSenseDocs
- 🐛 Issues: GitHub Issues
- RealSense team for the amazing hardware and SDK
- ROS2 community for robotics framework
- OpenCV and Open3D communities for computer vision tools
- All contributors and students of RealSense University
Ready to start your RealSense journey? 🚀