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The neuroscience, behaviour and ecology behind the development of an insect inspired visual collision detection mechanism

Lookup NU author(s): Dr Richard Stafford, Dr Claire RindORCiD


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In this talk we detail how we have developed a collision based sensor to detect automotive collisions. The sensor, which is suitable for VLSI implementation, is primarily based on the known neurobiology of the locust’s Lobula Giant Movement Detector (LGMD) neuron and its associated inputs. In this talk we present a holistic approach to the problem of developing the sensor. Firstly we review how the LGMD processes visual information. Next, before creating a biophysical computer simulation of the neuron, we study the behavioural responses of the locust caused by excitation in the LGMD. We also study the visual ecology of colliding objects encountered by the locust, and compare the visual environment of the locust to that which will be experienced by the artificial sensors. From this data we are able to show that a car collision detection mechanism based solely on the LGMD will be less robust than the predator avoidance role the neuron serves in the locust. However, we show that integrating the properties of the LGMD with directionally sensitive insect inspired neurons will create a robust system which can detect automotive collisions and ignore non collision scenes. We hypothesise that the predator avoidance properties of the LGMD may have evolved to exploit the unique visual niche encountered by the locust to fast moving, small predators and outline plans for further research into predator escape neurons based on co-evolution between predators and prey.

Publication metadata

Author(s): Stafford R, Rind FC

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: AVA Animal Vision Meeting

Year of Conference: 2005