Who this site is for
Students, makers, and researchers who want a guided path to build practical robotics systems instead of reading disconnected tutorials.
Robotics Learning Path
Build a Complete Robotics Project, Step by Step
A practical robotics course focused on ROS, perception, planning, simulation, manipulation, and deployment. Learn the engineering workflow from fundamentals to real robot systems.
8+
Core modules across the robotics stack
2
Languages: English and Simplified Chinese
ROS + AI
Engineering-focused lessons, not isolated notes
Sim-to-Real
From simulation prototypes to deployment
Project-based
Learn by building
Course scope
Perception, planning, control, deployment
What you will learn
Kinematics, ROS workflows, visual perception, planning, simulation, manipulation, reinforcement learning, and deployment architecture.
How the course is designed
The curriculum is structured around a complete engineering journey, so each module supports a real project objective.
Curriculum map
Core Modules
Use the homepage as a fast entry point, then dive into each section for theory, code, and hands-on workflows.
Math foundation
Robotics Basics
Build the mathematical foundation for robotics, including kinematics, dynamics, transformations, and DH parameters.
System integrationROS
Understand ROS communication, robot environment setup, and how perception components connect in practice.
Computer visionPerception
Learn object detection workflows, YOLO-based pipelines, and model training for robot vision tasks.
Virtual testingSimulation
Compare Gazebo, Drake, MuJoCo, and PyBullet for prototyping, validation, and physics-based testing.
Decision makingPlanning
Study task planning, temporal planning, reactive acting, and learning-enhanced planning methods.
Robot manipulationManipulation
Follow the MIT manipulation track covering pick and place, pose estimation, motion planning, and control.
Learning systemsReinforcement Learning
Explore RL fundamentals, value-based methods, policy gradients, and model-based approaches for robotics.
Sim-to-realDeployment
Move from simulation to real robots with hardware integration, architecture design, and safety considerations.
Roadmap
Recommended Learning Path
Start with setup, build foundations, then connect modules in an engineering workflow before moving into full deployment.
1
Get Ready
Set up Python and Linux basics so your development environment is ready for robotics practice.
2Build Foundations
Learn transformations, kinematics, dynamics, and coordinate systems before touching larger stacks.
3Enter the Workflow
Use ROS as the backbone, then connect perception, planning, simulation, learning, and deployment.
ROS
Perception
Simulation
Planning
Manipulation
Deployment
Approach
Why this course feels practical
Project-oriented structure
The site focuses on key ideas, curated references, and engineering context instead of duplicating every tutorial.
Designed for self-learners
Useful for beginners, graduation design, research prototypes, and makers building a full robotics stack.
Bilingual documentation
English and Chinese pages are maintained together so the site can serve both local learners and a wider learning community.
Activity
Latest Updates
2026-04-26
Updated the reinforcement learning, manipulation, planning, simulation, and deployment modules.
2025-12-16 to 2025-12-20
Initialized the ROS tutorial, added environment setup, Linux onboarding, and the first perception node workflow.
Continue learning
Learn Through Docs and Videos
Read the structured documentation, follow the roadmap, and watch hands-on videos for implementation details and project progress.
Robotics Course Docs
A bilingual robotics learning site covering ROS, perception, planning, simulation, manipulation, and deployment.
Robotics course docs for learners, makers, and researchers.
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