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Stephen Hausler is a Research Fellow working at the intersection of autonomous navigation and neuroscience. The objective of his research is to develop bio-inspired algorithms to enable robots to navigate autonomously, even in very challenging environmental conditions.
Stephen graduated from QUT with a Bachelor of Engineering with First Class Honours, majoring in Electrical Engineering, back in 2013. Since then, he has worked as both an Electronics Technician and an Electrical Engineer in a variety of roles and locations, including fly-in fly-out mining and industrial fertiliser manufacturing facilities. He began his PhD in 2018 and since then has published two journal articles and presented at several conferences. He completed his PhD in 2021.
He was also a grand finalist in the 2020 QUT Three Minute Thesis competition and has also been working as a Research Assistant on a collaborative project between QUT, iMOVE Australia, RACQ and TMR.
Publications
1) Multi-Process Fusion: Visual Place Recognition Using Multiple Image Processing Methods: https://ieeexplore-ieee-org.ezp01.library.qut.edu.au/document/8638528
2) Bio-inspired multi-scale fusion: https://link.springer.com/article/10.1007/s00422-020-00831-z
3) Filter Early, Match Late: Improving Network-Based Visual Place Recognition: https://ieeexplore-ieee-org.ezp01.library.qut.edu.au/document/8967783
Projects
- [COMPLETED] ARC Future Fellowship: Superhuman place recognition
- [COMPLETED] HD maps for automated driving
- AUSMURI: Neuro-Autonomy: Neuroscience-Inspired Perception, Navigation, and Spatial Awareness for Autonomous Robots
- Complementarity-Aware Multi-Process Fusion for Long Term Localization
- NVIDIA Applied Research Accelerator Program