Course overview
This course will provide training in rigorously applying mechatronic design principles to the development of a robotic system, incorporating the use of advanced control, signal processing and machine learning algorithms. Introduction to wheeled mobile robotics. Nonholonomic dynamics in Lagrangian formulation. Inertial navigation, including localisation and pose estimation by inertial sensing and Bayesian filtering. Image feature extraction. Motion control by visual servoing.
Course learning outcomes
- Given a design problem, identify and critically review relevant engineering literature for state-of-the-art solutions. (PLO 1, 2, 4, 5, 7) (EA 1.1-1.4, 2.1, 2.2, 3.2-3.5)
- Demonstrate proficiency in using the sensors and actuators on the given mobile robot platform, supported by a clear understanding of the physical principles and operational characteristics of the devices. (PLO 1, 2, 4, 5) (EA 1.1-1.4, 2.1, 2.2, 3.4, 3.5)
- Create mechanical designs in evolutionary iterations to integrate additional hardware components with the mobile robot platform, and determine the resultant system dynamics. (PLO 1, 4, 5) (EA 1.1-1.3, 2.1-2.3, 3.3)
- Implement inertial navigation and motion control on a mobile robot, with a clear understanding of the underlying theory and practical limitations. (PLO 1, 4, 5) (EA 1.1-1.3, 2.1-2.3, 3.3)
- Based on a top-down design, develop embedded software integrating application logic, information processing, sensing, actuation and communications, while demonstrating professional software development practices. (PLO 1, 4, 5, 7-9) (EA 1.1-1.3, 1.5, 2.1-2.4, 3.2, 3.3, 3.5, 3.6)
- Execute a holistic design-build-test plan using industry-standard tools, where modeling, model verification and simulation are embedded in the process. (PLO 1, 2, 4, 5, 9) (EA 1.1-1.5, 2.1-2.4, 3.3-3.5)
- Work independently and in a team, and communicate research and development outcomes through professional presentation and documentation. (PLO 1-9), (EA 1.x, 2.x, 3.x)