Year
2012
Units
4.5
Contact
1 x 2-hour lecture weekly
1 x 1-hour tutorial weekly
1 x 2-hour project work weekly
Prerequisites
1 1 of ENGR3771, ENGR3103
2 1 of ENGR3711, ENGR3504
3 Admission into MEB-Master of Engineering (Biomedical)
3a Admission into MEE-Master of Engineering (Electronics)
3b Admission into MESI-Master of Engineering (Smart Instrumentation)
3c Admission into GDPEB-Graduate Diploma in Engineering (Biomedical)
3d Admission into GDPEE-Graduate Diploma in Engineering (Electronics)
3e Admission into GCEB-Graduate Certificate in Engineering (Biomedical)
3f Admission into GCEE-Graduate Certificate in Engineering (Electronics)
3g Admission into GCESI-Graduate Certificate in Engineering (Smart Instrumentation)
3h Admission into HBSC-Bachelor of Science (Honours)
3i Admission into HBIT-Bachelor of Information Technology (Honours)
Must Satisfy: ((1 and 2) or ((3 or 3a or 3b or 3c or 3d or 3e or 3f or 3g or 3h or 3i)))
Enrolment not permitted
ENGR8503 has been successfully completed
Assumed knowledge
Students undertaking the one year honours programs should check to make sure they have the appropriate background from their undergraduate degrees.
Topic description
  1. Applications of Mobile Robots
  2. General Control schemes for Mobile Robots
  3. Navigation sensors, challenge of sensor noise
  4. Vision and Sonar based Perception, pose estimation
  5. Mobile robot localisation, belief representation, probabilistic map-based localisation and autonomous map building
  6. Path planning, Collision avoidance
Educational aims
Smart instrumentation systems are increasingly being deployed on autonomous (robotic) platforms where the robot is required to collect, process, analyse, and interpret sensory information without the intervention of a human operator. Typical examples include unmanned aerial, underwater, and terrain vehicles; marine probes; robotic surgical devices; automated biotissue diagnostic systems; etc.

This topic is designed to acquaint the student with the principles of designing robotic systems, and implementing the sensing capability and artificial intelligence (multiagent systems) necessary to allow the robot to behave autonomously using human like reasoning.
Expected learning outcomes
At the completion of the topic, students are expected to be able to:

  1. Have acquired experience in designing robotic systems
  2. Select appropriate microcontrollers, sensors, and actuators for construction of the robots according to specific requirements/considerations
  3. Program a robot to perform specific tasks
  4. Understand the theory and practical use of various approaches for implementing artificial intelligence in mobile robotic systems
  5. Develop strategies for linking multiple mobile robot systems so as to enable them to work collaboratively
  6. Design a mobile robot that can navigate and select appropriate routes autonomously
  7. Identify appropriate all-encompassing design solutions for given requirements
  8. Commence further industry / academic training in research and development in the field of computer architecture and other related disciplines
  9. Work independently and also as a member of a project team