We develop micro-robots that can inspect honeycomb cells with the aim of turning honeybee colonies into sensor networks for continuous, long-term ecological surveillance .
EU FP7 STRANDS
Tomáš Krajník
Associate Professor - Head of Lab
We aimed to develop robots capable to understand their environment and how it changes over time. This understanding enabled them to run for months in dynamic human environments.
STRANDS will produce intelligent mobile robots that are able to run for months in dynamic human environments. We will provide robots with the longevity and behavioural robustness necessary to make them truly useful assistants in a wide range of domains. Such long-lived robots will be able to learn from a wider range of experiences than has previously been possible, creating a whole new generation of autonomous systems able to extract and exploit the structure in their worlds.
Our approach is based on understanding 3D space and how it changes over time, from milliseconds to months. We will develop novel approaches to extract spatio-temporal structure from sensor data gathered during months of autonomous operation. Extracted structure will include reoccurring 3D shapes, objects, people, and models of activity. We will also develop control mechanisms which exploit these structures to yield adaptive behaviour in highly demanding, realworld security and care scenarios.
Researchers
Tomáš Krajník
Associate Professor - Head of Lab
