Improving Computational Thinking with Machine Learning and AI with Robotics

Purpose & objective

- Bring robotics technologies to the classroom or afterschool program to help improve computational thinking skills that can be transferred to the workforce.
- Learn about implementing technologies such as vision processing used in artificial intelligence.
- Learn about how image recognition and machine learning are combined in automation and manufacturing.
- Learn about how robotic competitions provide an opportunity for students to gain work-based learning skills transferrable to the workforce.

Outline

If selected, we would have 5 experimentation tables for different levels of engagement. Participants will be able to experiment and code an XRP robot to complete tasks to improve skills in algorithmic thinking.

Three substations will have three different tasks (drive forward and turn 5-10 min, 5-10 min line following, and 5-10 min distance detection). Participants will be guided on how the robot hardware receives data often abstracted in programming environments.

Participants will then be able to transition to the next station, where they can use a FIRST Tech Challenge robot to use image detection of April tags and a pre-built 3D image detection database (15 min). Participants will learn how databases and algorithms can have abstracted details that should be considered for modifying and utilizing algorithms.

In the last station, participants will be able to experiment with a machine learning toolchain kit where they can build their image detection models for a 3D printed object (30 min). Participants will learn the importance of the values that go into a data set to get an accurate recognition that robots can use to make decisions based on their environment.

Supporting research

https://ftc-docs.firstinspires.org/en/latest/apriltag/vision_portal/visionportal_overview/visionportal-overview.html

https://experientialrobotics.org/