Comparing simulation and physical kilobots performance in two ant-inspired foraging behaviours.

Robotics looks to nature for inspiration to perform effectively in unstructured environments and can be used to test biological hypotheses. Social animals often share information about food source locations like tandem running in ants, where a leader guides a naive recruit to a known profitable food site. This is extremely advantageous as it allows the sharing of important information among colony members, but it also has costs, such as waiting time inside the nest when no leaders are around, and a reduced walking speed for the tandem couple compared to individuals. Whether and when these costs outweigh the benefits is not well understood as it is challenging to study complex social behaviours in nature. We developed two kilobot-based approaches to compare tandem running and lone scout foraging (using an isotropic random walk) where an ant searches for food without any previous knowledge of its location: one approach based on real-life experiments and the other one on computer simulations. We tested whether the simulation-based comparison of the two bio-inspired strategies reliably predict the performance in the real-life scenario and we investigated the role that the size of the search arena played in the effectiveness of foraging. Tandem pairs discovered the food source faster in real-life experiments; however, this result was reversed in the simulations. These results highlight the inconsistencies between simulation and real-life experiments, previously reported for other systems and known as reality gap, and show how the use of simulations can lead to qualitatively different conclusions about the relative effectiveness of bio-inspired foraging strategies.