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A Metric for Hexagonal Grid-World Cooperative Object Recognition Tasks for a Swarm of Agents

In the future nano-robots could be used in in-vivo medical applications. By using lattice robots as a unit of measurement tumours could be assessed as malignant or benign by considering the shape of their boundaries through cooperative object recognition. With the objective of moving towards this end goal research has been carried out using simulations on hexagonal lattices that allow simple agents to cooperate to distinguish between two objects’ shapes. This paper determines a method which gives a value of difference between any two objects constructed on a hexagonal lattice. This difference value will provide a metric for future cooperative object recognition scenarios. The measure of the difference value was calculated considering varying degrees of knowledge about sections of the objects’ boundaries. The results were compared to a simulated task with agents that were homogeneous, anonymous, had a limited sensor range and no common coordinate system. It was found that the difference value metric provides a significant correlation to the time taken to complete a series of cooperative object recognition scenarios.