MEC 221 - Robotics and Controls

 
Description
This course builds on MEC 112,  Introduction to Robotics, through a series of hands-on exercises performed in the lab. Topics covered include fundamentals of comptuer vision: edge detection, lighting, neural networks and training data.  Students learn the process of inspecting robots for manufacturing, automated ground vehicles, as well as concepts of autonomy and path planning. Students program multiple robotic systems, including collaborative robots in real-world workcell configurations throughout this course. 

1. Simulate physical workcells using digital models.
2. Configure real-world workcell parameters using simulation data.
3. Interface robots to other devices using robot, digital, group and other types of I/O.
4. Describe the fundamentals of computer vision techniques.
5. Train a neural network to function as an object classifier.
6. Explain how systemic flaws in training data can produce artificial intelligence systems that have build-in bias.
7. Share program execution data with a Manufacturing Execution System (MES).
8. Troubleshoot issues with sensor data and data streams.

1. Computer vision
2. Collaborative robots
3. Object detection techniques
4. Path planning and autonomy
5. Integration with other systems
6. Neural networks and machine learning
7. Part inspection
8. Workcell design
9. Simulation software

• Information Literacy
• Technological Competence

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