Computer vision and robotics
R A Jarvis
3 points * 16 lectures, extensive reading * First semester * Clayton * Prerequisites: Level 2 substantially complete
Objectives The student is expected to acquire knowledge about the functional emulation of the visual capability of animals and humans through instrumentation and computational algorithmic methodology in the context of robotic guidance and develop initial judgement concerning the application scope of the various methodologies addressed.
Synopsis Human vision including optical illusions, image segmentation, consistent scene labelling, blocks world experiments, range-finding methodologies, 3D vision systems, semantic guidance and semantic-free systems; robotic hand/eye coordination; localisation, environmental modelling, path planning, complete robot navigation systems for indoor and outdoor application, natural landmark based robot navigation; application scope.
Assessment Examination (2 hours): 100%
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