ROS 2 Robotics Developer
Build the software real robots actually run on.
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Participants can interact with the instructor,
ask questions, seek clarification,
and receive immediate feedback. -
You can receive a full refund before
the second session. After attending
the second session, you will not be eligible
for a refund. -
Access to the session that was originally
conducted in real time. -
You can retake the same course you attended.
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We will provide you with the notes for the course.
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We will provide you with the homework
assignments for additional practice. -
You can always reach out to the instructor
between sessions or after the course on Slack.
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Upcoming Enrollment
November 1st - November 8th
0 sessions 6 hours each
Online, US Eastern Time
Build the software layer real robots actually run on.
Every robotics job posting asks for ROS 2. Almost nobody teaches it properly. What you'll find online is a wall of tutorials that get you to a talking turtle and then stop. You can follow all of them and still not be able to answer the question a robotics interviewer actually asks: your LiDAR is publishing and your transform tree is broken — what do you check first?
This course is 108 hours of answering that kind of question with your hands on a keyboard. You'll write publisher and subscriber nodes in Python and your first ones in C++. You'll define custom messages, run service and action servers, and fix the QoS mismatch that makes a topic publish into nowhere. You'll build a TF2 transform tree that keeps a LiDAR, an IMU, and a robot base honest about where they are relative to each other, and you'll debug it live in RViz2 rather than reading about it. You'll author a URDF model, drop it into Gazebo with working sensor plugins, and then do the thing most people skip: prove the simulation matches the real robot, by sending the same command to both and measuring the difference. You'll also write tests. In a field where most portfolios are a demo video and a prayer, a pytest suite is a hiring signal. You finish with a robot — physical or simulated — whose full sensor suite is correctly transformed and whose digital twin behaves like the real thing. And you finish with a title that stands on its own: ROS 2 Robotics Developer. No hardware required. The simulation track runs entirely on your laptop, anywhere in the world. This is the most common career move in robotics: software engineer to robotics engineer. This is the course that makes it.
Syllabus and Skills You Will Walk Away With
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1
Core ROS 2 Competency
- Build and maintain ROS 2 workspaces and packages, including multi-node launch file orchestration and parameter configuration
- Develop ROS 2 nodes in Python (rclpy), selecting appropriately between topics, services, and actions for a given communication pattern
- Design and debug TF2 transform trees to maintain correct spatial relationships across a multi-sensor robot
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2
Environment, Build System & Tooling
- Install and manage ROS 2 through Conda in an isolated environment, avoiding a system-wide install and keeping ROS versions reproducible across Linux, macOS, and Windows
- Define reproducible robotics environments via environment.yml / pinned channels so a workspace rebuilds identically on another machine
- Build multi-package workspaces with colcon, including --symlink-install development workflow, and resolve dependencies declared in package.xml
- Structure ament_python
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3
Node Development Using rclpy
- Implement ROS 2 publisher and subscriber nodes
- Build request/response services and long-running action servers and clients with feedback and goal cancellation
- Define custom interfaces
- Configure and tune QoS profiles (reliability, durability, history depth)
- Manage node parameters: declaration, runtime set/get, YAML parameter files
- Apply namespaces and topic remapping to run multiple instances of the same node in one graph
- Use executors and callback groups, multithread
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4
Sensor Integration & Perception Plumbing
- Integrate 2D LiDAR and IMU sensors into a ROS 2 graph, publishing correctly-framed and time-stamped sensor data
- Diagnose live robot state using RViz2 — transform errors, dropped topics, frame misalignment, sensor timing issues
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5
Simulation & Modeling
- Author URDF robot descriptions with accurate kinematics, joints, and collision geometry
- Build Gazebo simulation environments with configured sensor plugins (LiDAR, IMU, camera)
- Validate a simulated digital twin against physical hardware so the same ROS 2 commands produce matching behavior in both
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6
Runtime Introspection
- Inspect a live ROS 2 graph with the ROS2 CLI
- Visualize node and topic connectivity with rqt_graph to trace broken or mismatched connections
- Record and replay sensor data with ROS2 bag
- Work with ROS time and use_sim_time
- Use ROS 2 logging levels for structured runtime diagnostics
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7
Engineering Practice
- Work on a project
Schedule & Enrollment
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