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In recent years we've seen a proliferation of sensors and embedded computer systems in everyday devices, capable of capturing vast amounts of information in almost all areas of human activity - cars with GPSs and reverse-parking sensors, mobile phones with integrated cameras, outdoor lights that automatically come on at dusk. But the ready availability of such information does not ensure its efficient use, or that of the device that captures it. Professor Fabio Ramos' research aims to address this issue.
"For many years I've been intrigued with how humans can process so much information so quickly through their natural senses of vision, hearing, smell and so on. In an unconscious manner, everything we perceive is combined to create a seamless interpretation of our current environment or situation.
"I've been trying to replicate these capabilities in machines - from autonomous cars that can drive themselves to iron ore mines with multiple heavy automated vehicles and, in a new and exciting project, geophysical data collected from the entire continent being fused together to estimate potential locations for geothermal power plants.
"There's a lot of data out there. How best to make sense of it while understanding the relationships between different natural phenomena is what excites me about my research.
"One of my ultimate goals is to develop a robot that can learn about the world by experience, as a child does in the early stages of life. I'd also like to develop devices to help people with cognitive impairment (such as from dementia) to regain some of their independence.
"I've been working in this field since in 1997, and joined the University of Sydney in 2003. Through the Centre for Translational Data Science and the Australian Centre for Field Robotics, the University has given me excellent opportunities to develop my career."
In recent years we've seen a proliferation of sensors and embedded computer systems in everyday devices, capable of capturing vast amounts of information in almost all areas of human activity - cars with GPSs and reverse-parking sensors, mobile phones with integrated cameras, outdoor lights that automatically come on at dusk. But the ready availability of such information does not ensure its efficient use, or that of the device that captures it. Professor Fabio Ramos' research aims to address this issue.
"For many years I've been intrigued with how humans can process so much information so quickly through their natural senses of vision, hearing, smell and so on. In an unconscious manner, everything we perceive is combined to create a seamless interpretation of our current environment or situation.
"I've been trying to replicate these capabilities in machines - from autonomous cars that can drive themselves to iron ore mines with multiple heavy automated vehicles and, in a new and exciting project, geophysical data collected from the entire continent being fused together to estimate potential locations for geothermal power plants.
"There's a lot of data out there. How best to make sense of it while understanding the relationships between different natural phenomena is what excites me about my research.
"One of my ultimate goals is to develop a robot that can learn about the world by experience, as a child does in the early stages of life. I'd also like to develop devices to help people with cognitive impairment (such as from dementia) to regain some of their independence.
"I've been working in this field since in 1997, and joined the University of Sydney in 2003. Through the Centre for Translational Data Science and the Australian Centre for Field Robotics, the University has given me excellent opportunities to develop my career."
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2017 IEEE International Conference on Robotics and Automation (ICRA)pp.6381-6388, (2017)
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Journal of Field Roboticsno. 10 (2007): 849-861
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