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Endotracheal intubation is a critical medical procedure for protecting a patient’s airway. Current intubation technology requires extensive anatomical knowledge, training, technical skill, and a clear view of the glottic opening. However, all of these may be limited during emergency care for trauma and cardiac arrest outside the hospital, where first-pass failure is nearly 35%. To address this challenge, we designed a soft robotic device to autonomously guide a breathing tube into the trachea with the goal of allowing rapid, repeatable, and safe intubation without the need for extensive training, skill, anatomical knowledge, or a glottic view. During initial device testing with highly trained users in a mannequin and a cadaver, we found a 100% success rate and an average intubation duration of under 8 s. We then conducted a preliminary study comparing the device with video laryngoscopy, in which prehospital medical providers with 5 min of device training intubated cadavers. When using the device, users achieved an 87% first-pass success rate and a 96% overall success rate, requiring an average of 1.1 attempts and 21 s for successful intubation, significantly (P = 0.008) faster than with video laryngoscopy. When using video laryngoscopy, the users achieved a 63% first-pass success rate and a 92% overall success rate, requiring an average of 1.6 attempts and 44 s for successful intubation. This preliminary study offers directions for future clinical studies, the next step in testing a device that could address the critical needs of emergency airway management and help democratize intubation. 

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.