Long-range robotic imaging in participating media

Summary

This project will push the limits of long-range vision in participating media including fog and water, expanding the range of conditions under which robots can be safely deployed. Applications include all-weather autonomous driving, drone flight, and underwater survey.

Supervisor(s)

Dr Donald Dansereau

Research Location

Aerospace, Mechanical and Mechatronic Engineering

Program Type

Masters/PHD

Synopsis

Recent imaging advances emerging from the optics, computational imaging, and computer vision communities point the way forward for improving imaging through water, fog, rain, dust, and smoke. This project will jointly design optics and algorithms to deliver better perception in challenging, real-world robotic imaging scenarios.

Potential approaches include long-range ghost imaging, active and adaptive imaging, burst photography, light field video, single-photon avalanche diodes (SPADs), dynamic vision sensors, multispectral sensing, generalised structured light, time of flight, and LiDAR. Employing machine learning to make sense of novel imaging modalities can form a substantial aspect of this project, as can advancing a fundamental theory of information-driven camera evaluation and design.

Additional Information

Working within the Australian Centre for Field Robotics (ACFR), you will have access to the state-of-the-art robots, facilities, dedicated technical staff, and mentorship available through this world-class research centre. The ACFR undertakes significant field robotics programs in autonomous driving, flight, agriculture, and underwater survey, providing rich opportunities for deployment and validation of novel perception systems.

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Keywords

robotics, Imaging, Sensing, machine vision, computational imaging, Machine learning, autonomous driving, drone flight, underwater robotics, novel cameras

Opportunity ID

The opportunity ID for this research opportunity is: 2630

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