Nathan Bartlett


I was awarded my B.E. (Mechatronics) with first-class honours from the University of Newcastle, Australia, (Callaghan Campus) in May 2015. Between 2015 and 2019, I was the CTO of a deep-tech startup; with the aim to give autonomous vehicles human-like instincts. In 2016, I began my Ph.D in the field of Bayesian estimation, with a focus on Extended Target Tracking (ETT), and Simultaneous Localization and Mapping (SLAM).


My research interests are focused in Bayesian estimation and sensor fusion. My work is currently centered around the derivation of efficient ETT filters, which provide joint estimates of the target kinematic state and the target extent. I am now discovering new ways to apply these estimators to SLAM applications; enabling autonomous vehicles to make informed decisions in previously unexplored environments.


Between 2015 and 2019, I was the CTO of a deep-tech startup. During this period, I developed robust collision avoidance algorithms that can be utilized by both last-mile delivery vehicles and service robots within the agricultural sector. From this work, our startup was selected as finalists in the NEWi Awards for best smart city solution, and best startup in 2017 and 2018. I have also engaged with a local engineering firm (MRA), where I aided in the development of a three-dimensional mapping procedure using range-bearing sensors.


I have previously delivered course content within the Mechatronics Engineering program at the University of Newcastle. This includes presenting lectures within a Masters level course on advanced estimation, and running tutorials for a course that developed the necessary skills for students to model simple mechatronic systems.


Our background and vision


The research team


A list of research publications


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