Advanced Intelligent Robotics (12063.1)

This unit will provide students with an opportunity to integrate knowledge and skills of various data-driven approaches using machine learning to develop complex, intelligent robotic systems that integrate the perception of the environment around the robot, reason about current and future tasks, and plan their subsequent actions accordingly. Methods related to supervised, self-supervised, and generative machine learning approaches for robot design, kinematic and dynamic analysis, path and action planning, and optimal control of robots in a wide range of application scenarios from industry to healthcare, aged care, search and rescue, and home use will be discussed, implemented and evaluated. Furthermore, a focus will be on intelligent robotic systems that function appropriately in potentially unstructured and dynamic environments.

Learning outcomes

Upon successful completion of this unit, students will be able to:
1. Critically analyse, synthesise, and evaluate data-driven approaches using machine learning to develop complex intelligent robotic systems that integrate the perception of the environment around the robot, reasoning about current and future tasks, and planning of subsequent actions by the robot;
2. Develop and implement an intelligent robotic system that functions appropriately in potentially unstructured and changing environments for real-world applications of moderate complexity;
3. Demonstrate an advanced understanding and professional mastery of supervised, self-supervised, and generative machine learning approaches for robot design, kinematic and dynamic analysis, path and action planning, and optimal control of robots in a wide range of application scenarios from industry to healthcare, aged care, search and rescue, and home use; and
4. Make ethically, culturally and socially responsible decisions, and identify constraints, uncertainties and risks when defining system components and requirements of trusted autonomous intelligent robotic systems.

Graduate attributes

1. UC graduates are professional - communicate effectively
1. UC graduates are professional - display initiative and drive, and use their organisation skills to plan and manage their workload
1. UC graduates are professional - employ up-to-date and relevant knowledge and skills
1. UC graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
1. UC graduates are professional - work collaboratively as part of a team, negotiate, and resolve conflict
2. UC graduates are global citizens - adopt an informed and balanced approach across professional and international boundaries
2. UC graduates are global citizens - communicate effectively in diverse cultural and social settings
2. UC graduates are global citizens - think globally about issues in their profession
2. UC graduates are global citizens - understand issues in their profession from the perspective of other cultures
3. UC graduates are lifelong learners - reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development

Prerequisites

12061 Control Systems

Corequisites

None.

Incompatible units

None.

Equivalent units

None.

Assumed knowledge

None.