Robotics Curriculum & Courses

Sensors enable robots to perceive their environment and make autonomous decisions. In this unit, participants perform sensor integration, utilizing GPIO (General Purpose Input Output), digital inputs and outputs, an IMU (Inertial Measurement Units), motor encoders, IR (infrared) cameras, and LiDAR.

Participants compete in a 2v2 drone joust that rewards smart flying, power management, understanding of avionics sensors, and diligence in battery maintenance. Participants navigate challenges involving airflow disruption, ground/ceiling effects, and the tradeoff between speed and stability while utilizing optical flow sensors. This exercise promotes the practical application of drone control and teamwork under competitive conditions. 

Skills Developed: Maintainer habits, UAS operation, teamwork, power management. 

To prepare to navigate unknown environments, autonomous systems are often trained with data from known environments. This unit emphasizes the importance of data collection and labeling for applications like Collision Avoidance and Path Following. Participants will perform supervised learning techniques, utilizing Classification for detecting obstacles and Regression for path prediction. 

Participants autonomously navigate a static series of obstacles using simple command sequences. They plan flight paths, input sequential commands with a block-based IDE, and execute basic autonomous patterns (launch, wait, recover). This exercise emphasizes the importance of proportionality calculations and addresses the challenges of open-loop control. 

Skills Developed: Flight path planning, sequential command input, basic autonomous operation, proportionality calculations. 

AprilTags are a special type of marker that allows a robot to know its precise position (localization) and orientation (pose estimation) for accurate navigation. In this unit, participants calibrate the camera to improve AprilTag detection accuracy and leverage ROS (Robot Operating System) to perform waypoint navigation with the AprilTag markers. 

Simultaneous Localization and Mapping (SLAM) is a technique used in robotics to build a map of an environment while simultaneously keeping track of the robot's location within it. In this unit, participants configure ROS to communicate over a network, allowing the JetBot to transmit LiDAR data used to generate a high-fidelity map in an Ubuntu Virtual Machine.

Participants challenge each other to piloting or maintainer tasks of their own making. Themes for each day include flying challenges, teamwork challenges, head-to-head challenges, and troubleshooting and repair challenges. 

Skills Developed: Reinforcement of prior unit skills, including piloting, maintenance, teamwork, and troubleshooting. 

Reinforcement Learning is a type of machine learning where a robot learns to make decisions through trial-and-error. In Autonomous Racing, the robot learns through trial-and-error as it drives on the track. In this unit, participants collect data from the track, train and visualize the base model, and then provide feedback to the robot as it learns to race.

Participants work together to lift a payload using only their own drones. This exercise emphasizes mission planning, flight plan development, team coordination, and adapting to unexpected conditions. Students will calculate components of lifting force and understand how to sum and cancel force vectors from multiple sources. 

Skills Developed: Mission planning, flight plan development, team planning, coordinated multi-robot operation, considering risk, adapting to unexpected conditions, calculating relevant components of oblique forces. 

Python-based Coding Practice with Virtual SPIKE Prime provides students with a fully programmable robot that allows students to develop their programming and sensor integration skills using Python. The simulated environment is designed to resemble a robotics competition table, encouraging robotics teams to help prepare for competitions.

Block-based Coding Practice with Virtual SPIKE Prime provides students with a fully programmable robot that allows students to develop their programming and sensor integration skills using Blocks. The simulated environment is designed to resemble a robotics competition table, encouraging robotics teams to help prepare for competitions. 

Program the Strawberry Sorter to make decisions so that it can... sort strawberries! You will use if-then-else blocks to program simple decisions and looped decisions. The robot design for this unit is the Strawberry Sorter. 

Learn how to program Events with the Gyro Sensor! The robot build for this unit is Bot-it. 

In this unit, you will learn about the basics of electrical soldering and get comfortable with the tools. You will learn about soldering tools (soldering iron, solder, flux, etc.), soldering safety procedures, what makes a good solder joint (tinning, heating, applying solder), and checking continuity with a Multimeter.