This course will give students an in-depth perspective on the most advanced techniques and algorithms currently used in wheeled mobile, aerial, space, and ocean autonomous robots, working in unstructured environments. These techniques will include recent results from machine vision, robotic image and video processing, sensor-based control for autonomous robots, sensor fusion for robot pose estimation, advanced nonlinear motion estimation and control, simultaneous localization and mapping, learning and deep neural networks, perception and compliance of human behaviour, and advanced robotic trajectory tracking and path planning. Case studies of successful algorithms employed in single and multiple autonomous robots will be presented and discussed.

CILO-1: Apply mathematics, particularly in the areas of image processing, estimation and control, to design and develop efficient and reliable autonomous systems. CILO-2: Recognize, articulate, and address navigation and perception problems encountered in autonomous systems through the application of mathematics knowledge. CILO-3: Recognise the need for, and engage in life-long learning of autonomous systems and applications. CILO-4: Demonstrate competence in the application of advanced mathematics to analyze autonomous systems. CILO-5: Design and simulate autonomous systems using computer-aided simulation software.