Bio-Inspired Dual-Auger Vertical Self-Burrowing Robot: DEM-MBD Analysis of Downward Penetration in Granular Media

Abstract

Geotechnical engineering is crucial for infrastructure development, requiring precise subsurface investigation. Traditional penetration methods face increased difficulties and costs as effective stress rises with depth. In this paper, we present a bio-inspired robot capable of downward self-burrowing in granular media, drawing from nature's adaptive strategies in subterranean environments. We applied a coupled discrete element method (DEM) and multi-body dynamics(MBD) framework to analyze the self-burrowing behavior of the robot in dry sand. Using Project Chrono, an open-source physics engine, we integrated DEM for detailed soil-robot interaction modeling and MBD for the robot's dynamic response. The robot, inspired by awned seeds, features dual vertically aligned auger-shaped bodies connected to rotational motors, incorporating both contraction and extension mechanisms. Simulated in a packing of monodisperse frictional spheres, the interaction between the robot and sand is modeled with high fidelity. Our analysis focused on two operational cycles: Cycle 1 involves the rotation of the upper auger and contraction of the linear actuator, generating downward thrust. Cycle 2 involves the rotation of the lower auger and extension of the linear actuator, also generating downward thrust. Results indicate that the respective augers provide thrust during their active cycles and act as anchors during the other cycle. The robot's downward movement depends significantly on its initial embedment depth, with both upper and lower parts providing essential anchorage. At greater depths, the resistive forces and thrust forces increase, improving the robot's burrowing efficiency. Future work will identify the breaking points for optimal self-burrowing and further optimize the robot's design for various soil conditions.

This manuscript has been accepted for publication in GeoFrontiers 2025.