Lecture
Credit terms
-
End-term test – 50% to pass
-
Short tests at the end of lectures
-
Grades:
- 3.0: 50% – 59%
- 3.5: 60% – 69%
- 4.0: 70% – 79%
- 4.5: 80% – 89%
- 5.0: >= 90%
Lectures
- Introduction to the robotic programming environments
- Component-based approach for distributed control systems
- Communication protocols in distributed systems
- Introduction to ROS 2
- ROS 2: Mechanisms, Tools
- Simulation, Optimization, and Mathematical Libraries
- Control, Planning, and Navigation
Laboratory
Exercises
- L1 – Introduction
- L2 – Systems modeling
- L3 – Communication in distributed systems – MQTT
- L4 – Communication in distributed systems – ZeroMQ
- L5-L6 – Introduction to the ROS 2
- L7-L8 – Robot monitoring system in ROS 2
- L9-L10 – Simulation of the mobile robot in ROS 2
- L11- Mobile robot simulation with SciPy ODE solver
- L12 – Pose graph optimization with g2o
- L13 – Behavior Tree for a Pick-and-Place Task
- L14 – Robot navigation with ROS nav2 stack
- L.. – Simple optimization with CasADi
Credit terms
- Obligatory presence, one absence is allowed
- Preparation to classes
- Pass laboratory exercises (one of them can be skipped)