A comprehensive view of my research and development work across autonomous systems domains.
Developed mission-level autonomy for a self- and Earth-inspection payload on the Buccaneer Main Mission cubesat. Successfully integrated with orbiting satellite and secured $450k continuation funding.
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Leading R&D of mission autonomy for automated satellite rendezvous and servicing. Collaborating across sensing, perception, dynamics, and control teams. Completed CDR and presented at IAC 2025.
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Lead researcher integrating autonomous ground robots, drones, vehicle telemetry, and wearables for enhanced bushfire situational awareness. 15+ field trials, exhibited at RFS State Championships.
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Developed hierarchical planning framework for long-term autonomous operation with dynamic agents (people, livestock) and energy constraints. Published in IEEE Transactions on Field Robotics.
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Led GNC development for Rio Tinto's 'Dipper' robot, achieving centimetre-accurate positioning for blast hole inspection. Demonstrated in Pilbara, deployed in Utah. Instrumental in securing $16M continuation.
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Secured $200k ASA grant for developing intelligent prospecting algorithms for lunar rover missions. Created digital twin simulation and demonstrated on Swagbot platform.
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Led development of complete guidance, navigation, and control system for omni-directional wheeled mobile robots. Created simulation-to-deployment pipeline enabling multiple concurrent projects.
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Developed framework for capturing and conveying environment knowledge and dynamics. Applied to pasture forage monitoring for grazing livestock. Published in Journal of Field Robotics.
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Developed algorithms for simultaneously modelling multiple quantities of interest, leveraging relationships to maximise information gain. Published in RA-L, actively used in industry projects.
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Doctoral research on Efficient and safe path planning over rough terrains using terrain-dependent energy cost models and sampling-based planning techniques for long-duration autonomous missions on wheeled mobile robots.
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Doctoral research on receding horizon estimation and control strategies with structured noise blocking for accurate trajectory tracking of wheeled mobile robots operating in challenging off-road environments where wheel slip is prevalent.
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