Last modified: 22 Jul 2026 13:42
This course surveys many of the core problems of robotics, and their solutions. By the end of the course, a student should be able to program robots that move in predictable ways, overcoming environmental uncertainties; that can interpret their surroundings; and that can plan their motion in order to achieve goals. Topics covered include robot motion; image processing and computer vision; localisation methods and computer based search and planning. Apart from using programming skills to implement robot algorithms, the students will learn how to mathematically model robots in order to understand why robot algorithms are designed as they are.
| Study Type | Undergraduate | Level | 4 |
|---|---|---|---|
| Term | First Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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This course introduces the student to important problems, and their solutions, in the field of robotics. Topics include
- Robot motion
- Sensing
- Computer vision and image processing
- Localisation
- Search and planning
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 50 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Presentation (20 minutes) and Group Programming Project (Code and Report, 1500 words) worth 50% of the overall grade. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Analyse | Apply computer vision and sensor fusion algorithms to enable a robot to perceive and interact with its environment in an appropriate manner. |
| Conceptual | Analyse | Apply appropriate path finding algorithms and understand where they should be applied. |
| Conceptual | Apply | Understand how localisation can take place and be able to create and evaluate localisation algorithms. |
| Conceptual | Create | Be able to create a complete simulated robot and evaluate it within a simulation environment. |
| Assessment Type | Summative | Weighting | 50 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
2-hour exam worth 50% of the overall grade. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Analyse | Apply computer vision and sensor fusion algorithms to enable a robot to perceive and interact with its environment in an appropriate manner. |
| Conceptual | Analyse | Analyse how different choices with regards to robot platform and actuators affect robot freedom of movement. |
| Conceptual | Analyse | Apply appropriate path finding algorithms and understand where they should be applied. |
| Conceptual | Apply | Understand how localisation can take place and be able to create and evaluate localisation algorithms. |
| Conceptual | Create | Be able to create a complete simulated robot and evaluate it within a simulation environment. |
There are no assessments for this course.
| Assessment Type | Summative | Weighting | ||
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
2-hour exam. Best of (resit exam mark) or (resit exam mark with carried forward continuous assessment marks). |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Apply | Understand how localisation can take place and be able to create and evaluate localisation algorithms. |
| Conceptual | Analyse | Analyse how different choices with regards to robot platform and actuators affect robot freedom of movement. |
| Conceptual | Create | Be able to create a complete simulated robot and evaluate it within a simulation environment. |
| Conceptual | Analyse | Apply appropriate path finding algorithms and understand where they should be applied. |
| Conceptual | Analyse | Apply computer vision and sensor fusion algorithms to enable a robot to perceive and interact with its environment in an appropriate manner. |
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