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School of Engineering · ANU College of Systems and Society
This course is for graduate students interested in the fields of robot perception, motion planning, control theory, and autonomous systems. This course introduces students to the methodology and algorithms involved in the design and control of an autonomous race car. Topics include localisation, scan matching, PID control, mapping, learning based visual navigation, model-predictive control and ethical decision making. Students test and implement their algorithms in a racing sand-box.
Project Phase 1
Learning outcomes 1, 2
Project Phase 2
Learning outcomes 1, 2, 3
Project Phase 3
Learning outcomes 1, 2, 4
Reflection
Learning outcomes 5
Final Demonstration
Learning outcomes 1, 2, 3, 4
130 hours in total over the semester consisting of: - 12 × 2 hr Lectures/week - Self-directed learning as required. (130 hours in total)
None Preliminary Reading S. Thrun, W. Burgard, and D. Fox, Probabilistic Robotics, MIT Press, 2005.