Unearthing real-time 3D ant tunneling mechanics

Significance Predicting the stability of granular materials under particle removal has wide-reaching applications, including automating tunnel excavations. Searching for general laws that govern granular stability is challenging given the complexity of granular material dynamics. However, knowledge may be gained from the natural world, where organisms have evolved adaptive tunneling strategies. Among these, subterranean-nesting ants execute an innate tunneling behavioral program that can lead to remarkably stable tunnel excavation. We use X-rays to image the process of ant tunnel construction through a particulate substrate. We use these data to create a grain-scale accurate simulation for estimating particle mechanics in the sample during real-time excavation. We present evidence that ants benefit from force redistributions during incremental digging, suggesting techniques for robotic mining.