Target tracking is a complicated task from an engineering perspective, especially where targets are seen against complex natural scenery. Due to the high demand for robust target tracking algorithms much research has focused in this area. However most engineering solutions developed for this purpose are either unreliable in real world conditions or too computationally expensive to be used in many real-time applications. Insects, such as the dragonfly, solve this task when chasing tiny prey, despite their low spatial resolution eye and small brain suggesting that nature has evolved an efficient solution for target detection and tracking problem. This project aims to develop a robust, closed loop model inspired by the physiology of insect neurons that solves this problem, and to integrate this into an autonomous robot. This system is tested in software simulations using MATLAB/Simulink. In near future this system will be integrated with a robotic platform to examine its performance in real world environments to demonstrate the usefulness of this approach for applications such as wildlife monitoring.
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