Autonomous Systems Laboratory
Our research is in the areas of field robotics, sensor networks, and adaptive systems. We are developing new techniques for 3D perception and localisation, the autonomous control of machines, and the operation of large scale outdoor wireless sensor networks. Our key strength lies in combining these techniques to produce novel solutions to practical problems in fields such as environmental monitoring, agriculture, mining, manufacturing, and for the energy sector.
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We are developing technologies that will allow robotic systems to assist or replace humans performing tasks that are difficult, repetitive, unpleasant, or take place in hazardous environments. Our research focuses on methods for improving three-dimensional situational awareness, including sensing surroundings, constructing world models from sensor data, and detecting and interacting with obstacles and other moving objects. We focus on developing robust, reliable robotic systems that can operate for long periods in complex, dynamic, and unforgiving environments such as mine sites, industrial facilities, sub-sea oil fields, waterways, and low altitude airspace. |
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We are developing wireless sensor networks that will revolutionise the collection of data for applications such as environmental and infrastructure monitoring. These networks will provide long-term high quality, high resolution and low-cost data that will lead to improved management outcomes. Our research addresses the challenges of programming, deploying, and operating networks of many thousand of nodes over large geographical areas where the nodes must be able to run for many years without hands-on maintenance and using only power harvested from the environment (e.g. via solar panels). |
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Our research is concerned with recognising patterns and detecting events from data, as well as modeling and simulating complex self-organising systems. Techniques we have developed are being applied to the problems of detection of gas in underground coal mines, designing adaptive power grids, structural integrity modeling, optimal sensor configuration, and distributed fault detection and self-healing for wireless sensor networks. |
