Robotics Curriculum & Courses

In this unit, learners gain the essential setup skills for working with the Crazyflie platform. They assemble the drone, configure the software environment, attach sensing decks, and update firmware. After verifying stability with a grounded test, they complete a manual test flight before moving on. 

In this unit, learners explore assisted flight modes including altitude hold, hover, and position hold. Using the Flow Deck, they examine sensor-based stabilization and velocity control, and tune values in the PID controller to see how it affects the drone’s ability to correct and hold position. 

In this unit, learners set up and calibrate the Loco Positioning System, then use it to fly the Crazyflie through coordinate-based missions. They work with both TWR and TDoA modes and advance to multi-drone coordination, gaining firsthand experience with autonomous navigation and swarm operation. 

In this unit, participants perform a system validation by inventorying ShieldBot components and confirming their integrity through functional tests. They use structured checklists to verify that all hardware elements are present and operational, establishing a reliable foundation for the robotics build and programming phases. 

In this unit, participants assemble the ShieldBot robot by integrating its three core subsystems: Mobility, Power, and Control. They follow a structured build process and execute diagnostic programs to validate mechanical and electrical connections, ensuring the robot is ready for software development and autonomous behavior.

In this unit, participants integrate analog and digital sensors into the ShieldBot platform, including mechanical whisker switches and a phototransistor-based light sensor. They develop control logic to interpret environmental inputs and implement decision-making using conditionals, variables, and comparator structures in code. 

In this unit, participants explore how robots can detect and make decisions based on colored objects using the HuskyLens AI camera. Participants train the camera to recognize specific-colored objects and then modify code to respond with different, intelligent actions.

In this unit, participants learn to configure the HuskyLens AI camera to detect and track AprilTag markers. They explore how machine vision enables robots to identify specific tags and trigger programmed behaviors, supporting tasks like localization, positioning, and robot navigation.

In this unit, students learn to control the ShieldBot using an IR remote and receiver. They explore how IR signals work, program robot responses to remote buttons, and test range, interference, and line-of-sight. 

Pneumatic systems use compressed air to create robot motion through components such as reservoirs, valves, regulators, tubing, and cylinders. In this unit, participants will identify, assemble, test, and troubleshoot a basic pneumatic circuit, then integrate it as a controlled robot payload. 

3D Printing with Bambu Lab P2S

This badge is a sample activity from the full Coding and Computational Thinking with Virtual SPIKE Prime curriculum. In this activity, you will learn how to program the movement of a Virtual SPIKE Prime robot from directly within your web browser while completing challenges themed after the real-world Iris Rover from Carnegie Mellon University.

 This badge is a sample activity from the full Coding and Computational Thinking with Virtual SPIKE Prime curriculum. In this activity, you will learn how to program the movement of a Virtual SPIKE Prime robot from directly within your web browser while completing challenges themed after the real-world Iris Rover from Carnegie Mellon University.