Locust’s Looming Detectors for Robot Sensors
Visual systems in the animal kingdom are incredibly good at extracting useful information from what can often be a very complicated world. Many of these systems can provide inspiration for the design of our own ’seeing machines’ which we can then use in a variety of applications. Our own research is concerned with the detection of ’looming’ or motion in depth. Our biological inspiration is the locust, Locusta migratoria, which possesses two uniquely identifiable neurons (the LGMD and DCMD) that respond preferentially to movements directly towards the animal. The way in which these cells are able to identify such stimuli is now becoming well understood. As such, we have been able to create a plausible computational model of the afferent inputs to these neurons that has been shown to respond in a locust-like way to looming stimuli. This model is now being used to control the movements of a mobile robot within a simplified visual environment. We aim to continue the development of this model so that it may one day function within the same visual world as the locust itself.
KeywordsMobile Robot Optic Lobe Visual Environment Machine Vision System Direct Collision
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- Edwards DH (1982) The cockroach DCMD neurone. I. Lateral inhibition and the effects of light and dark adaptation. J Exp Biol 99: 61–90Google Scholar
- Harrison RR (2000) An analog VLSI motion sensor based on the fly visual system. PhD Thesis, Pasadena, California Institute of TechnologyGoogle Scholar
- Nilsson DE (1989) Optics and evolution of the compound eye. In: Stavenga DG, Hardie RC (eds) Facets of Vision. Springer-Verlag, BerlinGoogle Scholar
- Rowell CHF, O’Shea M, Williams JLD (1977) Neuronal basis of a sensory analyzer, the acridid movement detector system. IV. The preference for small field stimuli. J Exp Biol 68: 157–185Google Scholar
- Simmons PJ (1980) Connexions between a movement-detecting visual interneurone and flight motoneurones of a locust. J Exp Biol 86: 87–97Google Scholar
- Verschure PFMJ (1997) Xmorph: a software tool for the synthesis and analysis of neural systems. Technical report, Institute of Neuroinformatics, ZürichGoogle Scholar