Relational Database Management Systems (RDBMS)

Programme Outline

Learning Objectives and Structure

By the end of this course, learners can expect to:

Use mathematic tools to model and analysis systems and synthesise feedback controllers
Understand be able to design and analyse serial and parallel manipulators
Program and deploy robotic systems in Robot Operating System (ROS)
Understand and use fundamental concepts for contemporary robotics research and industry.
Be able to design a high-level structure of an arbitrary robotic system.
Understand the architecture of programmable industrial automation systems,
Get hands-on experience on the principles of developing functionality ox programmable automation using state machine models.
Understand and apply methods of software development based on state machine models.

Programme Structure: Participants will go through 4 days of training. Class will reconvene on the 5th day for a presentation as part of the course assessment.

Day 1

Mathematical Foundation (Differential Equations, Linear Algebra, Laplace Transform, Etc)
System Modelling
Dynamic Response
Stability
Automatic Controllers
Controller Tuning
Position and Velocity Control of DC Motor

Day 2

Kinematics and Dyanamics of Serial Manipulators
Kinematics and Dyanamics of Parallel Manipulators
Robot Operating System (ROS) Fundamentals and Hands On Operation

Day 3

Autonomous Mobile Robots – basic concepts
Mobile Robotic System General Structure
Robot Hardware – Mobility
Robot Hardware – Robot Sensing
Robot Hardware – Localisation
Robot Intelligence – Mapping
Robot Intelligence – SLAM
Robot Intelligence – Motion Planning
Robot Intelligence – Task Planning
Robot Fleet Management

Day 4

Automation systems – basic concepts
Computations in controllers
Different principles of automation application logic design
State based logic – basics
IEC 61499: main principles
State based logic – elevator use case
Implementation of state machines in IEC 61499 basic function blocks
State logic extensions

Day 5

Post-Assignment and Presentations

Assessment

Multiple methods of assessment are used to provide an opportunity for the participant to demonstrate their learning results with a variety of learning styles. These include:
• Pre-assignment due before class
• Class contribution
• In-session assignments (group work and presentations during the module)
• Take-home assignment after class

Subject Credits

Upon completion and satisfying the requirements of passing this course, learners will be awarded 12 subject credits.

What’s next

Find out more

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