Artificially Intelligent Machines - MTRN9222
Faculty: Faculty of Engineering
School: School of Mechanical and Manufacturing Engineering
Course Outline: MTRN9222 Course Outline
Campus: Sydney
Career: Postgraduate
Units of Credit: 6
EFTSL: 0.12500 (more info)
Indicative Contact Hours per Week: 3
Enrolment Requirements:
None
CSS Contribution Charge: 2 (more info)
Tuition Fee: See Tuition Fee Schedule
Further Information: See Class Timetable
View course information for previous years.
Description
The course is aimed at learning basic and advanced techniques necessary for the
sensing and control of autonomous systems. Contents covered in this course are the
theory and application of topics such as Stochastic Processes, State Estimation,
Sensor Data Fusion, Fuzzy Logic, Particle Swarm Optimization (PSO), Genetic
Algorithms. Half of the course is lecture-based. In the other half the students apply
the concepts on real data and a real platform (UGV -Unmanned Ground Vehicle).
sensing and control of autonomous systems. Contents covered in this course are the
theory and application of topics such as Stochastic Processes, State Estimation,
Sensor Data Fusion, Fuzzy Logic, Particle Swarm Optimization (PSO), Genetic
Algorithms. Half of the course is lecture-based. In the other half the students apply
the concepts on real data and a real platform (UGV -Unmanned Ground Vehicle).
Study Levels
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