Testing the reality gap with kilobots performing two ant-inspired foraging behaviours

Abstract

Robotics looks to nature for inspiration to perform effectively in unstructured environments and can be used as a platform to test biological hypotheses. Social animals often share information about food source locations: one example is 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 individual ants. Whether and when these costs outweigh the benefits is not well understood as it is challenging to observe complex social behaviours in nature. We developed two kilobot-based approaches to compare tandem running and lone scout foraging, where an ant searches for food without any previous knowledge of its location: one approach based on real-life experiments and one on computer simulations. We investigated the role that the size of the search arena played in the effectiveness of foraging. Tandem pairs were faster for all three arena sizes; however, this result was reversed in the simulations. These results highlight the inconsistencies between simulation and real-life kilobot experiments, previously reported for other systems and known as reality gap. Further testing is needed to inform on whether robotic applications should utilise agents with the same roles and capabilities for search, detection and repair-type tasks as simulations, or whether instead the two approaches should be treated separately.