AI and autonomy
Infusing individual and networked machines, agents, robots and drones with the ability to navigate and interact with their environment, make decisions and collaborate with each other.
This is a growing area of interest, stimulated in the general community by early developments in self-driving cars. Applications, however, are far more extensive, especially in the transport, manufacturing and agricultural sectors.
On offer are step changes in the ability of all forms of transport and robotic systems to function independently. Early examples are autonomous vehicles operating in mines and on farms. This is the core expertise of Melbourne’s Melbourne Information, Decision and Autonomous Systems – MIDAS.
Capabilities
- Agent planning and reasoning
- Team collaboration and optimisation
- Business process automation
- Sequential decision making
- AI for standalone autonomous systems
- Networked autonomous systems
Sectors
Mining, aviation, transport, manufacturing, agriculture, defence, food processing, medical diagnosis
UAV swarms reduced costs and expand operational coverage
Rather than using a central command to control unmanned autonomous vehicles (UAVs), a swarm approach has been developed to create an autonomous multi-robot network.
Smart home demonstrates AI algorithms ‘in the wild’
Using a smart home as a demonstration model, a methodology was established that allows an AI system to update the reasoning it uses to make decisions, incorporating previously unknown or novel situations.
