Dual-Auger Bio-Inspired Self-Burrowing Robot (BurroBot): Laboratory Evaluation of Horizontal Burrowing Behavior

Bio-inspired burrowing robots are emerging for underground exploration, site investigation, excavation, and search-and-rescue applications. Previous studies have proposed a dual-auger self-burrowing robot for horizontal penetration, utilizing Discrete Element Method–Multibody Dynamics (DEM–MBD) simulations to evaluate its performance. The augers mimic the coiling mechanism of Pelargonium seed awns or the spiral tail of spirillum bacteria, generating thrust through rotation. A central stator was previously used to counteract torque in the helical structure. However, horizontal burrowing presents two main challenges: (1) upward lift and (2) the need for a counter-torque mechanism. In this paper, we introduce a new-generation burrowing robot (BurroBot) and investigate its functionality through experimental testing. The redesigned robot features dual augers at both ends and a linear actuator in the middle, eliminating the need for a stator. We hypothesize that changing the auger handiness (i.e., opposite vs. same rotation directions) reduces the need for counter-torque, while the side-mounted linear actuator mitigates upward lift. The robot was tested in a container filled with poppy seeds and saturated sand, with its trajectory captured using a camera and processed with Python’s OpenCV library. Results compare the robot’s performance based on (1) different auger handiness configurations (opposite vs. same rotation directions) and (2) the presence vs. absence of the linear actuator in continuous rotation mode. Findings indicate that opposite auger handiness enables effective burrowing without requiring counter-torque, reducing rolling, while using a linear actuator significantly reduces uplift compared to relying solely on continuous auger rotation. The results show improvements in robot design for better control and functionality. The complexity of robot-granular media interactions requires further optimization for future generations of our robot.