Last modified: 23 Jul 2024 10:43
Mobile robots can be used in a range of applications, including warehouses, agriculture, and other real-world environments. One of the main challenges for robots operating in the real world is that this is an unstructured environment. Nature has found clever solutions for the design of intelligent and effective systems operating in the unstructured environment hence biology is an obvious source of inspiration for robotics. In this course we take inspiration from nature to engineer intelligent systems for real-world applications as, for example, locomotion.
| Study Type | Postgraduate | Level | 5 |
|---|---|---|---|
| Term | First Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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This course focuses on the foundations of mobile robots and bioinspiration. In the first part, the course covers topics such as actuation, perception, localisation and mapping. It also features algorithms that enable the motion control and coordination of multi-robot systems. The course will include practical sessions with hands-on robot programming using a differential robot car platform. The students will also work with a simulation environment.
The second part of the course introduces bioinspiration as a method to tackle the challenges of real world, unstructured environments. The aims of this part of the course are: i) Explain the benefits and limitations of bio-inspired approaches for robotic applications; ii) Extract basic principles from intelligent systems in nature that can be applied to mobile robotics; iii) Using bioinspiration, embodied intelligence and self-organisation as driving forces towards a successful implementation of robotics in unstructured environments.
Main topics
Course content
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 70 | |
|---|---|---|---|---|
| Assessment Weeks | 16 | Feedback Weeks | 17,18,19 | |
| Feedback |
Feedback will be given together with marked assignment. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Apply | Apply notions of control architectures, perception and actuation to control robot systems. |
| Conceptual | Evaluate | Assess the benefits and limitations of bioinspired locomotion, swarm intelligence, soft robotics. |
| Conceptual | Evaluate | Discuss the impact of bioinspiration, embodied intelligence, self-organisation on robot systems. |
| Procedural | Apply | Perform simple localisation and navigation with real or stimulated robot systems. |
| Procedural | Create | Implement bioinspired swarm robotics and multi-robot systems algorithms. |
| Assessment Type | Summative | Weighting | 30 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
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There are no assessments for this course.
| Assessment Type | Summative | Weighting | ||
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Apply | Perform simple localisation and navigation with real or stimulated robot systems. |
| Conceptual | Evaluate | Discuss the impact of bioinspiration, embodied intelligence, self-organisation on robot systems. |
| Procedural | Create | Implement bioinspired swarm robotics and multi-robot systems algorithms. |
| Conceptual | Evaluate | Assess the benefits and limitations of bioinspired locomotion, swarm intelligence, soft robotics. |
| Conceptual | Apply | Apply notions of control architectures, perception and actuation to control robot systems. |
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