Building EMERGENCE.
A multidisciplinary team working across robotics, reinforcement learning, embedded systems, electrical engineering and physical platform development.
- Oversee and facilitate team progress.
- Design and maintain physical systems.
“I started EMERGENCE because I want to contribute to something larger than myself — helping build the systems that could push humanity toward its next great chapter beyond Earth.”
- Create and maintain the ROS2 system.
- Deploy ROS2 and software on robot platforms.
- Simulate robot platforms in Gazebo.
“I joined EMERGENCE because I have always been interested in space exploration. I love the idea of an autonomous construction swarm, especially after seeing them in movies, and I’m excited at the opportunity to contribute my skills to a project like this.”
- Design and create the first reinforcement learning algorithm for a single robot platform.
- Create a simple environment to train the AI in.
“I joined EMERGENCE because of the curiosity about exploring worlds beyond Earth. My childhood dream was to become an astronaut, but when I realised that might not be my path, I became fascinated by robots building the infrastructure that makes off-world exploration possible.”
- Assist in creating the first reinforcement learning algorithm for a single robot platform.
- Create a probabilistic environment to train the AI within.
“I joined EMERGENCE to learn more about how reinforcement learning changes when multiple agents have to learn and work together, and to solve the challenges that come with it.”
- Design and maintain electrical systems.
- Set up and maintain communication between the SBC and MCU.
“I joined EMERGENCE because I want to continue developing in embedded systems and control. I’m especially interested in how hardware, control, and autonomous systems work together, and I think this project is a good chance for me to build on my previous experience and learn more in this area.”
EMERGENCE is a project within Monash DeepNeuron.
Monash DeepNeuron is a student team focused on improving the world through Artificial Intelligence and Optimised Computing.
Dedicated to the exploration and advancement of Artificial Intelligence and Optimised Computing, Monash DeepNeuron brings together students, researchers and industry collaborators through hands-on technical projects and research.
Technical Teams
Technical teams work with researchers across a range of fields to develop custom AI and optimised-computing solutions and compete in international competitions.
Non-Technical Teams
Non-technical teams focus on education, accessibility and community engagement, helping people participate in AI and optimised computing regardless of prior experience.
The team also works to build collaborative networks between students, academic staff and industry partners, with a focus on ethical, meaningful research and practical technical development.
Through outreach and educational initiatives, DeepNeuron aims to make AI and optimised computing more understandable and accessible to the wider community.
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