SpatioTemporal
[Adjective] Relating to both space and time.
SpatioTemporal is an Australian research company building foundation models for Physical AI.
Founded in Melbourne, we develop compact foundation models and operating systems for robotics – with research spanning motion, intent, human-robot interactions and consequence modelling.
Our first foundation model, LSTM-01, established Motion Intelligence as the first Large SpatioTemporal Model. We are now expanding the technical programme through simulation, benchmarking, multi-agent research and collaboration with robotics and Physical AI partners.
Research with a path to deployment.
SpatioTemporal sits at the intersection of machine learning, robotics and human behaviour. We are deliberately not building robots, vehicles or autonomy stacks. We build intelligence that can integrate with them.
Our current work combines foundational research with practical evaluation: developing models, testing them in simulation, establishing benchmarks, and working with partners to understand where Motion Intelligence can improve real autonomous systems.
TEAM
AB – Andrew Ballard
Matt Dickinson
Professor Alan Duffy
Andrew is the founder of SpatioTemporal and architect of its Motion Intelligence research. His background spans robotics, engineering, spatial systems, human-machine teaming and applied Defence AI research. He developed the LSTM-01 architecture and leads SpatioTemporal’s research, technical strategy and demonstrations.
Matt is SpatioTemporal’s COO and operating partner, with senior delivery and commercial experience across major Australian telecommunications and utility organisations. He leads commercialisation, partnerships, operations and investor process, with a focus on moving SpatioTemporal’s research into practical evaluation and integration.
Alan is an astrophysicist, science communicator and Pro Vice-Chancellor at Swinburne University of Technology. He advises SpatioTemporal on scientific strategy, research framing and institutional collaboration, bringing deep experience across research, technology and public science.
Building with the Physical AI ecosystem.
We work with robotics companies, simulation platforms, researchers and technology partners to evaluate Motion Intelligence in increasingly realistic environments.
We are particularly interested in collaborations involving simulation, human-robot interaction, autonomous vehicles, robotics evaluation and integration with existing perception and planning systems.
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