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Mr Adam Jacobson

Science and Engineering Faculty,
Electrical Engineering, Computer Science,
Robotics and Autonomous Systems

Personal

Name
Mr Adam Jacobson
Position(s)
Research Fellow
Science and Engineering Faculty,
Electrical Engineering, Computer Science,
Robotics and Autonomous Systems
Discipline *
Artificial Intelligence and Image Processing, Electrical and Electronic Engineering
Email
Location
View location details (QUT staff and student access only)
Qualifications

Bachelor of Engineering (Electrical) (Queensland University of Technology)

* Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2008

Biography

My PhD research developed novel biologically-inspired algorithms for fusing and calibrating multiple sensors for deployment within robotic Simultaneous Localisation And Mapping (SLAM) applications.  This work developed techniques which removed difficult calibration procedures from deploying robotic platforms in new environments and enabled the integration of multiple low-cost sensors into a single unifying framework to enable localisation and navigation of robotic platforms within difficult environmental conditions.

As a Research Fellow with QUT, I have worked on projects including developing “An Infinitely Scalable Learning and Recognition Network” and creating “Automation Enabling Positioning for Underground Mining”.

The Infinitely Scalable Learning and Recognition Network project is funded by the Asian Office of Aerospace Research and Development and is a collaboration between Harvard University, University of Notre Dame and QUT. The project develops novel algorithms to compress information to enable large-scale learning and recall of places around the world.

The Automation Enabling Positioning for Underground Mining project is a collaboration between Caterpillar, Mining3, Advance Queensland and QUT seeking to develop algorithms which enable the positioning of vehicles in underground mines using low-cost cameras and lasers. The project seeks to overcome the many challenges of working and navigating within an underground environment including dynamic lighting conditions, environment conditions, dust and occlusions.

 

 

This information has been contributed by Mr Adam Jacobson.