Basic information
- Field of study
- AGH UST International Courses
- Major
- All
- Organisational unit
- AGH University Database of Electives
- Study level
- University database of electives
- Form of study
- Full-time studies
- Profile
- General academic
- Didactic cycle
- 2026/2027
- Course code
- UBPOJOS.A200000.20182.26
- Lecture languages
- English
- Mandatoriness
- Elective
- Block
- General Modules
- Course related to scientific research
- Yes
- USOS code
- 130-INT-xS-308
|
Period
Summer semester
|
Method of verification of the learning outcomes
Exam
Activities and hours
Laboratory classes:
15
Project classes: 15 |
Number of ECTS credits
4
|
Goals
| C1 | Introduce students to the fundamental principles of mobile robotics, navigation and robot perception. |
| C2 | Provide knowledge of local and global path planning methods, SLAM techniques and robot sensors. |
| C3 | Develop practical skills in programming mobile robots and implementing navigation algorithms in simulation and on real robotic platforms. |
Course's learning outcomes
| Code | Outcomes in terms of | Learning outcomes prescribed to a field of study | Methods of verification |
|---|---|---|---|
| Knowledge – Student knows and understands: | |||
| W1 | fundamental concepts of mobile robots and application areas. | Project, Report, Test results, Presentation | |
| W2 | principles of robot sensing, localization, mapping and navigation. | Project, Report, Test results, Presentation | |
| W3 | methods of local and global path planning and SLAM algorithms. | Project, Report, Test results, Presentation | |
| Skills – Student can: | |||
| U1 | U1 program mobile robots and use robotic software frameworks. | Project, Report, Test results, Presentation | |
| U2 | implement and evaluate local and global path planning algorithms in simulation environments. | Project, Report, Test results, Presentation | |
| U3 | configure and apply selected SLAM methods. | Project, Report, Test results, Presentation | |
| U4 | prepare an engineering project concerning autonomous navigation. | Project, Report, Test results, Presentation | |
| Social competences – Student is ready to: | |||
| K1 | work in teams during engineering tasks involving robotics systems. | Project, Presentation | |
| K2 | critically evaluate developed solutions and justify design decisions. | Project, Presentation | |
| K3 | present, showcase, and defend the developed solution to a given problem | Project, Presentation | |
Program content ensuring the achievement of the learning outcomes prescribed to the module
The course provides practical knowledge and engineering skills in the field of mobile robotics. Students become familiar with robot programming, navigation algorithms, localization and mapping methods, and deployment of autonomous systems. The module combines laboratory exercises with project classes, where students design and implement a mobile robot navigation system in simulation and validate selected elements on real robotic platforms
Student workload
| Activity form | Average amount of hours* needed to complete each activity form | |
| Laboratory classes | 15 | |
| Project classes | 15 | |
| Preparation of project, presentation, essay, report | 60 | |
| Preparation for classes | 30 | |
| Student workload |
Hours
120
|
|
| Workload involving teacher |
Hours
30
|
|
* hour means 45 minutes
Program content
| No. | Program content | Course's learning outcomes | Activities |
|---|---|---|---|
| 1. |
The laboratory classes combines short theoretical introductions, computer programming exercises, simulation tasks and selected experiments on real robotic platforms to provide both conceptual understanding and practical skills. Topics cover: 1. Mobile robots basic concepts 2. Robot programming and software tools 3. Robot sensors and perception 4. Local path planning methods 5. Global path planning methods 6. Simultaneous localization and mapping (SLAM) 7. Mission planning and validation on real robots |
W1, W2, W3, U1, U2, U3, K1 | Laboratory classes |
| 2. |
Students carry out projects focused on designing and evaluating a navigation system for a mobile robot using simulated environments. Projects may involve localization, mapping, local and global path planning. Each group defines the project objective and scope, selects methods and tools, and develops the solution under instructor supervision.
The project workflow includes: Problem definition and requirements analysis. Simulation environment preparation. Implementation of selected navigation modules. Testing and parameter tuning. Evaluation of results. Preparation of technical report and final presentation. |
W1, W2, W3, U1, U2, U3, U4, K1, K2, K3 | Project classes |
Extended information/Additional elements
Teaching methods and techniques :
Discussion, E-learning, Case study, Flipped classroom, Project Based Learning, Demonstration, Workshop
| Activities | Methods of verification | Credit conditions |
|---|---|---|
| Lab. classes | Report, Test results | Positive grade from laboratory tasks |
| Project classes | Project, Report, Presentation | Positive grade from completed project (report + oral presentation) |
Conditions and the manner of completing each form of classes, including the rules of making retakes, as well as the conditions for admission to the exam
by personal arrangement with course leader and lecturers
Method of determining the final grade
the weighted average of grades from project classes (35%), laboratory classes (35%), exam (30%) - exam must be passed to pass the course.
Manner and mode of making up for the backlog caused by a student justified absence from classes
by personal arrangement with course leader and lecturers
Literature
Obligatory- Thrun, S.; Burgard, W.; Fox, D. Probabilistic Robotics; Intelligent robotics and autonomous agents; MIT Press: Cambridge, Massachusetts London, 2006.
- Siegwart, R. Introduction to Autonomous Mobile Robots, 2nd ed.; Intelligent robotics and autonomous agents series; MIT Press: Cambridge, Massachusetts, 2011
- Barfoot, T. State Estimation for Robotics, Second edition.; Cambridge University Press: Cambridge, United Kingdom New York, NY, USA, 2024
- Choset, H. M. Principles of Robot Motion: Theory, Algorithms, and Implementations; Intelligent Robotics and Autonomous Agents Ser; MIT Press: Cambridge, 2014
Scientific research and publications
Research- Autonomous navigation
- Localization and mapping
- Koszyk, J., Hyla, B., Pieczonka, L., Ambroziński, L., 2026. Multi-sensor robotic mapping with thermal and acoustic imaging for non-contact technical diagnostics. Eksploatacja i Niezawodność – Maintenance and Reliability. https://doi.org/10.17531/ein/217575
- Pargieła, K., Jasińska, A., Malczewska, A., Grzelka, K., Koszyk, J., Ambroziński, Ł., 2025. Application of mobile laser scanner to augment stationary collected point clouds. Building Research & Information 53, 675–699. https://doi.org/10.1080/09613218.2025.2451975
- Koszyk, J., Jasińska, A., Pargieła, K., Malczewska, A., Grzelka, K., Bieda, A., Ambroziński, Ł., 2024b. Semantic Segmentation-Driven Integration of Point Clouds from Mobile Scanning Platforms in Urban Environments. Remote Sensing 16, 3434. https://doi.org/10.3390/rs16183434
- Hyla, B., Koszyk, J., Ambroziński, Ł., Pieczonka, Ł., 2024. Zrobotyzowany system inspekcyjny do detekcji anomalii termicznych i akustycznych w obiektach technicznych. Badania Nieniszczące i Diagnostyka 10, 14–18. https://doi.org/10.26357/BNiD.2024.006