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MEEN41440

Academic Year 2025/2026

Robotic Applications (MEEN41440)

Subject:
Mechanical Engineering
College:
Engineering & Architecture
School:
Mechanical & Materials Eng
Level:
4 (Masters)
Credits:
5
Module Coordinator:
Assoc Professor Nikolaos Papakostas
Trimester:
Spring
Mode of Delivery:
Blended
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

The primary objective of this module is to provide a hands-on course in robotics and digital technologies used in robotic and automation applications. Particular emphasis is placed on programming, testing and operating commercial industrial and collaborative robots, sensors, end effectors and platforms in the context of realistic applications often met in manufacturing environments. This course does not require any previous knowledge in the area of robotics.
Modern Industry 4.0 technologies, including digital twin and process simulation tools will be demonstrated during the course.

About this Module

Learning Outcomes:

On completion of this module students should be able to:
1. Understand the fundamental principles underlying robotic technologies.
2. Critique and be able to explain the role of Industry 4.0 technologies in robotics cell design and analysis.
3. Apply the steps of a robotic cell design project in a lab environment.
4. Develop and test robotic applications in a lab environment.
5. Realise the basic capabilities of modern robotic technologies and applications.
6. Demonstrate a high level of competency in understanding the basic requirements of novel automation projects where robots are planned to be introduced.
7. Understand the health & safety regulations and related standards underlying the operation of robotic equipment in industrial applications.
8. Make purchase / maintenance decisions using techno-economical models.

Indicative Module Content:

Topic 1: Module Outline and Introduction to Robots and Applications
Topic 2: Foundations and Motion
Topic 3: Robot Arm Kinematics and Simulation
Topic 4: Manipulator Velocity Dynamics and Control
Topic 5: Mobile Robots
Topic 6: Computer Vision: Light, Colour, Images
Topic 7: Image Processing
Topic 8: Image Feature Extraction
Topic 9: Cameras and Other Sensors
Topic 10: Invited Lecture

Student Effort Hours:
Student Effort Type Hours
Lectures

24
Laboratories

8
Specified Learning Activities

30
Autonomous Student Learning

63
Total

125

Approaches to Teaching and Learning:
active/task-based learning
lectures
lab work
group work

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Exam (In-person): Final exam End of trimester
Duration:
2 hr(s)
 Standard conversion grade scale 40% No
55
 No
Group Work Assignment: Group project Week 3, Week 4, Week 5, Week 6, Week 7, Week 8, Week 9, Week 10, Week 11, Week 12 Standard conversion grade scale 40% No
45
 No

Carry forward of passed components
Yes
 

Resit In Terminal Exam
Summer Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Group/class feedback, post-assessment
• Self-assessment activities

How will my Feedback be Delivered?

Feedback will be provided to students regarding their group assignments. Personalised feedback can be provided as part of a series of quizzes.

Robotics, Vision and Control (Fundamental Algorithms in MATLAB), P. Corke, W. Jachimczyk, R. Pillat, 3rd Edition, Springer, 2023
Robotics, Vision and Control (Fundamental Algorithms in Python), P. Corke, 3rd Edition, Springer, 2023
Introduction to Robotics, J. Craig, 4th Global Edition, Pearson, 2021
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