ECEN 430 [Draft subject to Auditing]

For academic year 2019

Advanced Mechatronic Engineering 2: Intelligence and Design

This course provides a guide to advanced techniques in the field of Mechatronics. The course material studies the interaction between hardware, software and communication components as it relates to embedded systems. Robotics are frequently used to illustrate the mechatronic theory. Artificial Intelligence techniques are introduced as a practical method for addressing the complex interactions between the electronic, mechanical and software components. The course is very practically oriented and primarily uses project-based assessments. These include a robotic competition, real-world customer design, industrial design considerations and cognitive robotics.

The following is the material to be covered during the lectures:

Robotic Systems

Robotic Operating System

Robot Kinematics

slam for dummies.pdf

How a Kalman filter works, in pictures _ Bzarg.pdf

Control Architectures

  • Mechatronic Specifications (skip the font and first-person advice!) Including: Design to Customer Specification, Human Interaction, Industrial Design & Design Life Cycle

Kinect Intro

Stereo Vision cameras

Learning Objectives*


Formulate appropriate task-solving strategies based on advanced Mechatronic techniques, such as analytical design. Much of the course is based on simulated and physical autonomous Mobile Robotics, the application will be applicable to a wide range of devices. Engineering judgement applied to mechatronic device construction and final design critique. The course considers the advanced programming and user considerations required for practical mechatronic devices. 3(b). [Examined in Assessment 1]


Integrate wider considerations than functionality, such as the role of customer, assembly and construction into designs. Design, demonstrate and present the above aspects of Advanced Mechatronics, including to external customers and important dignitaries 3(f). [Examined in Assessment 2 & 3]


Evaluate the impact of mechanical constraints in relation to operation and programming a device, i.e. investigate a robotic system. 3(e). [Examined in Assessment 1]


Use means like Kalman filter to handle error propagation & uncertainty; part of Simultaneous Localisation & Mapping. Define sensing, control of high-level behaviour. Categorise reactive & high-order deliberative behaviour viz localisation, mapping, path planning & goal setting. Use the capabilities in control architecture. Use high-order deliberative control, e.g. A*path planning, vector field histogram and cognitive control, i.e. affective computation 3(f). [Examined in Assess 1]


Synthesise, specify, select and utilise a wide range of artificial intelligence techniques in order to solve complex control problems that would otherwise be impractical using conventional mathematical approaches. 3(f). [Examined in Assessment 2 if most appropriate design method]

Teaching format

During the trimester there will be two lectures and one tutorial or group meeting per week.