Search for: All records

Underground construction and tunnel excavation are known to redistribute stresses and cause ground displacement. Analytical solutions for stress distribution typically break down at shallow depths or in soil masses that exhibit high spatial variability, making numerical simulations necessary. Seeking to find new geometries and excavation strategies for underground construction, we propose to look to nature for inspiration. We extract 3-D digital twins of Florida Harvester ant (Pogonomyrmex Badius) structures from a nest cast in situ and simulate the stress and displacement fields around that nest with the Finite Element Method (FEM). Stress invariants around the main shaft are compared to those around idealized geometric representations of that shaft, i.e. helixes with a fixed pitch angle and a uniform elliptical cross-section. Helical structures made of circular cross-sections and horizontally oriented elliptical cross-sections interact in a way that reduces the risk of tension failure and distributes the shear stress more evenly. One can show that in addition to the extra stability that they offer and the lower risk of tensile or shear failure that they exhibit, helical shafts have the advantage of requiring less power to excavate than straight sub-vertical shafts. 

Robotic navigation on land, through air, and in water is well researched; numerous robots have successfully demonstrated motion in these environments. However, one frontier for robotic locomotion remains largely unexplored—below ground. Subterranean navigation is simply hard to do, in part because the interaction forces of underground motion are higher than in air or water by orders of magnitude and because we lack for these interactions a robust fundamental physics understanding. We present and test three hypotheses, derived from biological observation and the physics of granular intrusion, and use the results to inform the design of our burrowing robot. These results reveal that (i) tip extension reduces total drag by an amount equal to the skin drag of the body, (ii) granular aeration via tip-based airflow reduces drag with a nonlinear dependence on depth and flow angle, and (iii) variation of the angle of the tip-based flow has a nonmonotonic effect on lift in granular media. Informed by these results, we realize a steerable, root-like soft robot that controls subterranean lift and drag forces to burrow faster than previous approaches by over an order of magnitude and does so through real sand. We also demonstrate that the robot can modulate its pullout force by an order of magnitude and control its direction of motion in both the horizontal and vertical planes to navigate around subterranean obstacles. Our results advance the understanding and capabilities of robotic subterranean locomotion.