Target detection: neural networks, behaviour and biomimetic applications. This project aims to understand the neural and behavioural mechanisms that allow insects to efficiently detect moving targets in visual clutter, despite being equipped with small brains and low-resolution eyes. The project is expected to generate fundamental knowledge using a unique combination of quantitative behaviour, neurophysiology, pharmacological intervention and biomimetic modelling. Expected outcomes include an in ....Target detection: neural networks, behaviour and biomimetic applications. This project aims to understand the neural and behavioural mechanisms that allow insects to efficiently detect moving targets in visual clutter, despite being equipped with small brains and low-resolution eyes. The project is expected to generate fundamental knowledge using a unique combination of quantitative behaviour, neurophysiology, pharmacological intervention and biomimetic modelling. Expected outcomes include an increased understanding of neural mechanisms underlying sensory selectivity, the development of novel techniques, and enhanced capacity for interdisciplinary collaborations. The project will provide significant knowledge as the developed biomimetic algorithms should be applicable for increased performance in drones or other unmanned vehicles.Read moreRead less
Life or death decisions: making fast, accurate choices in a complex world. This project aims to understand how hoverflies and honey bees, with tiny brains and sensory systems, excel at making fast and accurate decisions while on the fly in a complex world. The project will combine brain recordings with flight analyses and computational modelling to generate new knowledge on how animals may utilize movements to simplify information sampling. Expected outcomes are a novel, comprehensive understand ....Life or death decisions: making fast, accurate choices in a complex world. This project aims to understand how hoverflies and honey bees, with tiny brains and sensory systems, excel at making fast and accurate decisions while on the fly in a complex world. The project will combine brain recordings with flight analyses and computational modelling to generate new knowledge on how animals may utilize movements to simplify information sampling. Expected outcomes are a novel, comprehensive understanding of how animal movements could enhance decision speed and accuracy. This should provide substantial benefits for neuroscience, and for enhancing performance of autonomous robotic systems operating in challenging environments, such as disaster relief, mining and remote exploration. Read moreRead less
Strategies for mid-air collision avoidance in aircraft: lessons from bird flight. Birds seldom collide with each other and other objects, despite the high speeds at which they fly in complex environments. This project will examine how birds sense and avoid impending collisions, and will use these results to design novel strategies for the detection and avoidance of aircraft mid-air collisions.