IN2106 Intelligent Machine Programming Lab
| Lecturer (assistant) | |
|---|---|
| Number | 0000002313 |
| Type | practical training |
| Duration | 6 SWS |
| Term | Summer semester 2025 |
| Language of instruction | English |
| Position within curricula | See TUMonline |
Admission information
Description
In this course, we offer the student clear, intensive guidance to robot programming and low to high-level control design. The focus at the beginning of this course is to familiarize students and make them user-ready for different types of robotics systems, e.g., Universal Robots UR10e or UR5e. In particular, students at the beginning of the course will be taught rules about working with robots (safety aspect, best positioning for shutdown mode, etc), an introduction to ROS, and then a quick overview of available robots. We use RoboDK for the simulation and offline programming of industrial robots (RoboDK Offline Robot Simulator https://robodk.com). Later in the course, and for each of the Robotics systems used in this course, an overview of its components (controller, hardware, and control panel), connection/setup, and interface medium will be explained to the students. The rest of the course will focus on writing codes and programming the robot to perform a certain number of tasks that range from simple to complex.
Prerequisites
- Fundamentals of control theory
- Fundamentals of robotics
- C,C++
- Python
- Fundamentals of robotics
- C,C++
- Python
Teaching and learning methods
During the lectures, students are instructed in a teacher-centered style. In the lab, students will perform several experiments and solve various assignments. In particular:
• Lectures (for direct transfer of theoretical knowledge)
• Lab assignments (for testing the learned approaches)
• Final task (to evaluate whether students can transfer the methods they have learned during the course and applied to the real-life complex tasks)
• Lectures (for direct transfer of theoretical knowledge)
• Lab assignments (for testing the learned approaches)
• Final task (to evaluate whether students can transfer the methods they have learned during the course and applied to the real-life complex tasks)