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Module: Control, Planning, and Decision-Making (Part 1)
| Study level | Bachelor | |
| ECTS credits | 1 ECTS | |
| Study forms | Hybrid or fully online | |
| Module aims | Provide a comprehensive understanding of control and planning strategies for autonomous systems, emphasizing both classical and AI-based paradigms. Students will explore how control algorithms translate high-level planning decisions into safe and precise vehicle motion under real-world uncertainties. The module highlights the integration of feedback control, optimization, and learning-based techniques to ensure stability, robustness, and adaptability in dynamic environments. Practical focus is given to hybrid control architectures, motion planning, and behavioral decision-making for safe autonomy. | |
| Pre-requirements | Motivation to study AV, recommended to have basics on programming, electronics and mechatronics | |
| Learning outcomes | After completing this module (for every topic listed below), the student: - knows x - knows y - understands z - can w |
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| Topics | Topic AV1 (1 ECTS) Topic AV2 (2 ECTS)) Topic AV3 (2 ECTS) Topic AV4 (1 ECTS) |
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| Type of assessment | The prerequisite of a positive grade is a positive evaluation of module topics and presentation of practical work results with required documentation | |
| Learning methods | to be added | |
| AI involvement | Explicit list of AI tools and application mtehods | |
| References to literature | to be added | |
| Lab equipment | to be added | |
| Virtual lab | to be added | |
| MOOC course | ||
